TEAMSchools/teamster
Feb 2025 – Jun 2026
14 Months active
Languages Used
SQLYAMLPythonMarkdownJSONJavaScriptBash
Technical Skills
Data EngineeringETLSQL DevelopmentCI/CD ConfigurationData ModelingData Warehousing
Cristina Baldor
PROFILE
Cristina Baldor
Over 14 months, contributed to TEAMSchools/teamster by engineering robust analytics and data infrastructure, focusing on data modeling, pipeline reliability, and governance. Delivered features such as unified data models, attendance and assessment analytics, and point-in-time reporting, using SQL, dbt, and Cube.js to support scalable BI and compliance needs. Addressed data quality and access control through schema refactors, YAML standardization, and integration with Google Cloud Platform. Enhanced reporting accuracy and maintainability by implementing rigorous testing, documentation, and code hygiene practices. The work enabled more reliable dashboards, streamlined onboarding for new engineers, and established a foundation for evolving academic-year and attendance analytics.
Overall Statistics
Feature vs Bugs
52%Features
Repository Contributions
294Total
Bugs
92
Commits
294
Features
100
Lines of code
356,729
Activity Months14
Your Network
11 peopleShared Repositories
11
Anthony WaltersMember
Anthony WaltersMember
Anthony WaltersMember
cbaldorMember
Cristina BaldorMember
Charlie BiniMember
Casey GibsonMember
Gaby RangelMember
Kevin VerhoffMember
Work History
June 2026
67 Commits • 21 Features
Jun 1, 2026June 2026 monthly summary for TEAMSchools/teamster: Key work focused on making analytics time-aware, governance-aligned, and production-stable. Highlights include Cube snapshot enhancements with an anchor guard and CA/truancy measures, AY labeling, and the integration of academic_year_label into dim_dates with exposure in attendance views, supported by updated tests and documentation. Significant stability and correctness improvements were achieved through fixes such as suppressing sqlfluff LT01 in is_week_end_record, reworking the enrollment/attendance spine with a boundary-union approach, and routing attendance status through the enrollment-grain rollup. Additional impact came from DBT and cube semantic-layer expansion (administration_dates, assessments, and student_assessments cubes; student_enrollment_status), plus tooling and playbook improvements for dev/test workflows. Overall impact: higher data quality, more reliable year-over-year analytics, and a scalable foundation for evolving academic-year semantics across dashboards, APIs, and analysts’ workflows.
67 Commits • 21 Features
Jun 1, 2026June 2026 monthly summary for TEAMSchools/teamster: Key work focused on making analytics time-aware, governance-aligned, and production-stable. Highlights include Cube snapshot enhancements with an anchor guard and CA/truancy measures, AY labeling, and the integration of academic_year_label into dim_dates with exposure in attendance views, supported by updated tests and documentation. Significant stability and correctness improvements were achieved through fixes such as suppressing sqlfluff LT01 in is_week_end_record, reworking the enrollment/attendance spine with a boundary-union approach, and routing attendance status through the enrollment-grain rollup. Additional impact came from DBT and cube semantic-layer expansion (administration_dates, assessments, and student_assessments cubes; student_enrollment_status), plus tooling and playbook improvements for dev/test workflows. Overall impact: higher data quality, more reliable year-over-year analytics, and a scalable foundation for evolving academic-year semantics across dashboards, APIs, and analysts’ workflows.
June 2026
May 2026
42 Commits • 13 Features
May 1, 2026Monthly summary for 2026-05 focusing on business value and technical achievements across TEAMSchools/teamster: Key features delivered and major fixes: - Admin Directory API: Correct scope for groups lookup fixed to ensure proper access when listing user groups (admin.directory.group.readonly for groups.list). This prevents unauthorized access and aligns with Admin SDK permissions, reducing risk of failed group lookups in cube features. - Attendance data model and CA metrics: Added chronic absenteeism and ADA tier to the attendance fact; restructured fct_student_attendance_daily with CTEs to expose running sums and is_chronically_absent and ada_tier; introduced enroll_status filtering to CA metrics to align with Tableau, and updated related measures (pct_tardy, pct_ontime) for accuracy across dashboards. - Attendance cube exposure and governance: Exposed attendance cube members publicly for view access across related cubes (attendance, attendance_detail, dim_dates), and updated view exposure in joined cubes to ensure dashboards can safely read current data without exposing sensitive joins. - Lattice extracts improvements: Updated Lattice user roster filter and SFTP path for extracts; expanded inclusion criteria (Terminated staff with 30-day lookback, specific titles/locations) and updated destination path to production, improving data timeliness and completeness for HR analytics. - Point-in-time dimensional enhancements: Added point-in-time dims for ELL, IEP, and meals to attendance-related views; replaced current-state attributes with dimensional history to support accurate year-long reporting and cross-report consistency. Major bugs fixed and stability improvements: - Admin Directory API categories: Correct scope usage prevented mispermissions in groups lookup. - Attendance: Ensured visibility and consistent access across attendance-related cubes; fixed public exposure and joined cube access to avoid misreads in dashboards. - Lattice roster extraction: Corrected intern filtering and roster scope to produce accurate headcount in downstream analytics. Overall impact and business value: - Improved data correctness, access governance, and dashboard reliability, enabling faster decision making and more trustworthy analytics for student performance, CA compliance, and HR operations. - Reduced risk of permission errors and data leakage by aligning scopes and exposure with intended access policies. - Increased data timeliness and coverage for population analytics (Lattice, attendance, and roster extracts), supporting better workforce planning and policy evaluation. Technologies and skills demonstrated: - Cloud-based data stack and BI integration (DBT, cube, Cloud Run concepts via MCP docs), SQL optimization, and data modeling (attendance_fact, dim tables, and running windows). - Version control discipline (co-authored commits across multiple features and fixes). - Data governance and documentation practices, including scope clarification and design specs for MCP deployments and access controls. - Collaborative development across squads, with robust test and validation patterns for complex join paths and date-range semantics.
May 2026
42 Commits • 13 Features
May 1, 2026Monthly summary for 2026-05 focusing on business value and technical achievements across TEAMSchools/teamster: Key features delivered and major fixes: - Admin Directory API: Correct scope for groups lookup fixed to ensure proper access when listing user groups (admin.directory.group.readonly for groups.list). This prevents unauthorized access and aligns with Admin SDK permissions, reducing risk of failed group lookups in cube features. - Attendance data model and CA metrics: Added chronic absenteeism and ADA tier to the attendance fact; restructured fct_student_attendance_daily with CTEs to expose running sums and is_chronically_absent and ada_tier; introduced enroll_status filtering to CA metrics to align with Tableau, and updated related measures (pct_tardy, pct_ontime) for accuracy across dashboards. - Attendance cube exposure and governance: Exposed attendance cube members publicly for view access across related cubes (attendance, attendance_detail, dim_dates), and updated view exposure in joined cubes to ensure dashboards can safely read current data without exposing sensitive joins. - Lattice extracts improvements: Updated Lattice user roster filter and SFTP path for extracts; expanded inclusion criteria (Terminated staff with 30-day lookback, specific titles/locations) and updated destination path to production, improving data timeliness and completeness for HR analytics. - Point-in-time dimensional enhancements: Added point-in-time dims for ELL, IEP, and meals to attendance-related views; replaced current-state attributes with dimensional history to support accurate year-long reporting and cross-report consistency. Major bugs fixed and stability improvements: - Admin Directory API categories: Correct scope usage prevented mispermissions in groups lookup. - Attendance: Ensured visibility and consistent access across attendance-related cubes; fixed public exposure and joined cube access to avoid misreads in dashboards. - Lattice roster extraction: Corrected intern filtering and roster scope to produce accurate headcount in downstream analytics. Overall impact and business value: - Improved data correctness, access governance, and dashboard reliability, enabling faster decision making and more trustworthy analytics for student performance, CA compliance, and HR operations. - Reduced risk of permission errors and data leakage by aligning scopes and exposure with intended access policies. - Increased data timeliness and coverage for population analytics (Lattice, attendance, and roster extracts), supporting better workforce planning and policy evaluation. Technologies and skills demonstrated: - Cloud-based data stack and BI integration (DBT, cube, Cloud Run concepts via MCP docs), SQL optimization, and data modeling (attendance_fact, dim tables, and running windows). - Version control discipline (co-authored commits across multiple features and fixes). - Data governance and documentation practices, including scope clarification and design specs for MCP deployments and access controls. - Collaborative development across squads, with robust test and validation patterns for complex join paths and date-range semantics.
April 2026
35 Commits • 8 Features
Apr 1, 2026April 2026 monthly summary for TEAMSchools/teamster: Delivered high-impact data integrity work, platform feature delivery, and governance improvements across surveys tooling, Google AppSheet onboarding, Cube infrastructure, and security policies. Emphasis on business value, reliability, and maintainable architecture.
35 Commits • 8 Features
Apr 1, 2026April 2026 monthly summary for TEAMSchools/teamster: Delivered high-impact data integrity work, platform feature delivery, and governance improvements across surveys tooling, Google AppSheet onboarding, Cube infrastructure, and security policies. Emphasis on business value, reliability, and maintainable architecture.
April 2026
March 2026
23 Commits • 4 Features
Mar 1, 2026March 2026 monthly summary for TEAMSchools/teamster focused on delivering a unified data model, a robust state assessments analytics foundation, and improved data governance to enable faster, more reliable BI.
March 2026
23 Commits • 4 Features
Mar 1, 2026March 2026 monthly summary for TEAMSchools/teamster focused on delivering a unified data model, a robust state assessments analytics foundation, and improved data governance to enable faster, more reliable BI.
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026: Focused on improving data model reliability and maintainability for the TEAMSchools/teamster repo by standardizing YAML formatting across teammate models. Delivered a targeted formatting cleanup that reduces ambiguity in field descriptions and simplifies future changes. No major bugs reported or fixed this month for this repo. These changes reduce onboarding time for new teammates and lower the risk of YAML-related misconfigurations in production.
1 Commits • 1 Features
Feb 1, 2026February 2026: Focused on improving data model reliability and maintainability for the TEAMSchools/teamster repo by standardizing YAML formatting across teammate models. Delivered a targeted formatting cleanup that reduces ambiguity in field descriptions and simplifies future changes. No major bugs reported or fixed this month for this repo. These changes reduce onboarding time for new teammates and lower the risk of YAML-related misconfigurations in production.
February 2026
January 2026
2 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for TEAMSchools/teamster: Delivered two SQL readability and style improvements to standardize coding across the analytics layer, enhancing maintainability and reducing onboarding time for new or cross-functional engineers. No major bugs fixed this period; effort focused on code hygiene and consistency across fct_teammate_attrition and dim_teammates models, with direct commits enabling traceability. This work supports more reliable analytics delivery and quicker future feature integration.
January 2026
2 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for TEAMSchools/teamster: Delivered two SQL readability and style improvements to standardize coding across the analytics layer, enhancing maintainability and reducing onboarding time for new or cross-functional engineers. No major bugs fixed this period; effort focused on code hygiene and consistency across fct_teammate_attrition and dim_teammates models, with direct commits enabling traceability. This work supports more reliable analytics delivery and quicker future feature integration.
November 2025
5 Commits • 1 Features
Nov 1, 2025November 2025 (TEAMSchools/teamster) — Delivered critical data model and reporting enhancements, stabilized data pipelines by reverting a semantic-layer change, and performed branch cleanup to remove an extraneous SQL file. Business value: improved data integrity, reporting accuracy, and query performance; reduced maintenance risk and increased confidence in dashboards for leadership and product teams. Demonstrated robust SQL/data modeling skills and disciplined version control across the repo.
5 Commits • 1 Features
Nov 1, 2025November 2025 (TEAMSchools/teamster) — Delivered critical data model and reporting enhancements, stabilized data pipelines by reverting a semantic-layer change, and performed branch cleanup to remove an extraneous SQL file. Business value: improved data integrity, reporting accuracy, and query performance; reduced maintenance risk and increased confidence in dashboards for leadership and product teams. Demonstrated robust SQL/data modeling skills and disciplined version control across the repo.
November 2025
October 2025
23 Commits • 11 Features
Oct 1, 2025October 2025 (2025-10) monthly summary for TEAMSchools/teamster. Delivered a mix of feature enhancements, schema cleanups, and targeted bug fixes that improved data integrity, scheduling reliability, and overall developer productivity. The team also exercised careful change management around roster changes to minimize front-end disruptions and conflicts.
October 2025
23 Commits • 11 Features
Oct 1, 2025October 2025 (2025-10) monthly summary for TEAMSchools/teamster. Delivered a mix of feature enhancements, schema cleanups, and targeted bug fixes that improved data integrity, scheduling reliability, and overall developer productivity. The team also exercised careful change management around roster changes to minimize front-end disruptions and conflicts.
September 2025
27 Commits • 9 Features
Sep 1, 2025September 2025 monthly summary for TEAMSchools/teamster: Delivered significant enhancements to the Calculation Engine, enabling more accurate candidate scoring, projections, and synthesis of snapshot and current tracker outputs. Implemented Data Transformation & Cleaning to normalize data by unnesting recruiters and subjects and trimming unnested subjects, improving data quality and downstream analytics. Strengthened testing and data model integrity with dedicated enhancements (one row per application and goal tests) and ongoing code health improvements. Replaced a broken timeline with a robust Live View, enabling real-time insight for stakeholders. Enabled period-based analysis and tracking improvements by adding start_date and end_date for joins and introducing current week handling with adjusted join logic. Maintained stability and maintainability through lint/config cleanup and routine bug fixes across the data pipeline.
27 Commits • 9 Features
Sep 1, 2025September 2025 monthly summary for TEAMSchools/teamster: Delivered significant enhancements to the Calculation Engine, enabling more accurate candidate scoring, projections, and synthesis of snapshot and current tracker outputs. Implemented Data Transformation & Cleaning to normalize data by unnesting recruiters and subjects and trimming unnested subjects, improving data quality and downstream analytics. Strengthened testing and data model integrity with dedicated enhancements (one row per application and goal tests) and ongoing code health improvements. Replaced a broken timeline with a robust Live View, enabling real-time insight for stakeholders. Enabled period-based analysis and tracking improvements by adding start_date and end_date for joins and introducing current week handling with adjusted join logic. Maintained stability and maintainability through lint/config cleanup and routine bug fixes across the data pipeline.
September 2025
August 2025
32 Commits • 13 Features
Aug 1, 2025Month: 2025-08 Overview: In August 2025, the TEAMSchools/teamster work focused on strengthening data reliability, expanding analytics coverage, and stabilizing the reporting path. The team delivered core data pipeline enhancements, improved data modeling for broader categorization, and initial metrics exposure, while also elevating code quality to support long-term maintainability. Key features delivered: - Data source integration for SchoolMint Grow Dash to enable end-to-end data flow from source systems. (commit a4715772bb0d28564a4c0a7d030a6b42e5bcdc64) - Staffing model id and entity mapping to support broader categorization and analytics. (commit 0f13d5176d9c9d9beb8cb69b1cd5d438258c7475) - Initial metric view to surface core metrics, providing early visibility into performance indicators. (commit a9af8ab02fa851d84bd94e9f04680a250cbd38de) - Staging: include all fields to ensure complete data capture for downstream reporting, improving data completeness. (commit 2de4605fa7581646f660da7762fbfcc682bfd45f) - Date spine integration for snapshots and joins to enable consistent temporal analysis; followed by status and join refinements during the month. (commits af00cb159e587d59219f69a3e8d81d429902a9e1, b5e866ec8c5485113948e707914fdcf0929dadaa, 2fda8fbda504bc6c832d9c8215a709b11cf5dc60) - Code quality and formatting cleanup, including YAML formatting for consistency and general code formatting improvements. (commits 16541a84bf737dc79d0a13e2066f506cd279ed12, d0efbe667889bfdd76c561d5d54bf760fecee403) Major bugs fixed: - Hardcoded academic year value causing data alignment issues fixed. (commit cc9dc204e02af04b21e9d165917cf8a62b6f0b48) - Join logic on date fields corrected to ensure accurate data relationships. (commit f56e8f55f9e869e9adf94fac3045c855d51cb19e) - Investigated and stabilized reporting path to address user-reported troubles and stabilize outputs. (commit 3793e6daaad3a0428baeb14c13d96a8698812c36) - Cascading status propagation fixed to ensure consistent status across related entities. (commit 8fc62edfc2422d1a7f260398c570b874c57c88a2) - Cascade calculation logic corrected to improve accuracy of cascade metrics. (commit 4dc092b369d57a8dfal498872615cb8818779d53) Overall impact and accomplishments: - Enhanced data reliability and completeness, enabling more trustworthy dashboards and reports. Core metrics surfaced earlier, reducing manual remediation and enabling faster decision-making. Stabilized reporting paths lowered rework in downstream analytics and improved cross-system data integrity. The work set a strong foundation for future cross-entity analytics and SLA-aligned reporting. Technologies/skills demonstrated: - Data modeling and ETL design adjustments (staffing model id, entity mapping) - Data quality, debugging, and issue stabilization (join fixes, trouble in reporting, cascade fixes) - Snapshotting and temporal data handling concepts (date spine integration and joins) - Code quality, formatting, and YAML standardization for maintainability - End-to-end feature delivery with measurable business impact (dashboard data source, metrics view, staging completeness)
August 2025
32 Commits • 13 Features
Aug 1, 2025Month: 2025-08 Overview: In August 2025, the TEAMSchools/teamster work focused on strengthening data reliability, expanding analytics coverage, and stabilizing the reporting path. The team delivered core data pipeline enhancements, improved data modeling for broader categorization, and initial metrics exposure, while also elevating code quality to support long-term maintainability. Key features delivered: - Data source integration for SchoolMint Grow Dash to enable end-to-end data flow from source systems. (commit a4715772bb0d28564a4c0a7d030a6b42e5bcdc64) - Staffing model id and entity mapping to support broader categorization and analytics. (commit 0f13d5176d9c9d9beb8cb69b1cd5d438258c7475) - Initial metric view to surface core metrics, providing early visibility into performance indicators. (commit a9af8ab02fa851d84bd94e9f04680a250cbd38de) - Staging: include all fields to ensure complete data capture for downstream reporting, improving data completeness. (commit 2de4605fa7581646f660da7762fbfcc682bfd45f) - Date spine integration for snapshots and joins to enable consistent temporal analysis; followed by status and join refinements during the month. (commits af00cb159e587d59219f69a3e8d81d429902a9e1, b5e866ec8c5485113948e707914fdcf0929dadaa, 2fda8fbda504bc6c832d9c8215a709b11cf5dc60) - Code quality and formatting cleanup, including YAML formatting for consistency and general code formatting improvements. (commits 16541a84bf737dc79d0a13e2066f506cd279ed12, d0efbe667889bfdd76c561d5d54bf760fecee403) Major bugs fixed: - Hardcoded academic year value causing data alignment issues fixed. (commit cc9dc204e02af04b21e9d165917cf8a62b6f0b48) - Join logic on date fields corrected to ensure accurate data relationships. (commit f56e8f55f9e869e9adf94fac3045c855d51cb19e) - Investigated and stabilized reporting path to address user-reported troubles and stabilize outputs. (commit 3793e6daaad3a0428baeb14c13d96a8698812c36) - Cascading status propagation fixed to ensure consistent status across related entities. (commit 8fc62edfc2422d1a7f260398c570b874c57c88a2) - Cascade calculation logic corrected to improve accuracy of cascade metrics. (commit 4dc092b369d57a8dfal498872615cb8818779d53) Overall impact and accomplishments: - Enhanced data reliability and completeness, enabling more trustworthy dashboards and reports. Core metrics surfaced earlier, reducing manual remediation and enabling faster decision-making. Stabilized reporting paths lowered rework in downstream analytics and improved cross-system data integrity. The work set a strong foundation for future cross-entity analytics and SLA-aligned reporting. Technologies/skills demonstrated: - Data modeling and ETL design adjustments (staffing model id, entity mapping) - Data quality, debugging, and issue stabilization (join fixes, trouble in reporting, cascade fixes) - Snapshotting and temporal data handling concepts (date spine integration and joins) - Code quality, formatting, and YAML standardization for maintainability - End-to-end feature delivery with measurable business impact (dashboard data source, metrics view, staging completeness)
May 2025
1 Commits
May 1, 2025Month: 2025-05 focused on correcting teammate name representation in reporting for the TEAMSchools/teamster repo. Implemented a SQL query refactor to consistently use the current teammate name across all records. Removed the legacy teammate field from the initial SELECT and re-added it in subsequent sections to ensure the most up-to-date name is reflected. This standardization improves data integrity for teammate-based metrics in downstream dashboards and reports. Resulted in more trustworthy analytics, reduced need for manual data cleaning, and smoother reporting cycles. Technical approach prioritized minimal risk by isolating the change to the data extraction path and validating against existing reporting queries.
1 Commits
May 1, 2025Month: 2025-05 focused on correcting teammate name representation in reporting for the TEAMSchools/teamster repo. Implemented a SQL query refactor to consistently use the current teammate name across all records. Removed the legacy teammate field from the initial SELECT and re-added it in subsequent sections to ensure the most up-to-date name is reflected. This standardization improves data integrity for teammate-based metrics in downstream dashboards and reports. Resulted in more trustworthy analytics, reduced need for manual data cleaning, and smoother reporting cycles. Technical approach prioritized minimal risk by isolating the change to the data extraction path and validating against existing reporting queries.
May 2025
April 2025
22 Commits • 12 Features
Apr 1, 2025Monthly summary for 2025-04 for TEAMSchools/teamster: Delivered a substantial feature and reliability package, enabling richer analytics, automated data ingestion, and stronger governance. Key work spanned data model enhancements for demographics, cross-survey analytics, integration work, scheduling, security, and multiple reliability fixes that reduce operational risk and improve reporting accuracy. Business impact includes improved data quality, faster, more trustworthy insights, and lower maintenance overhead.
April 2025
22 Commits • 12 Features
Apr 1, 2025Monthly summary for 2025-04 for TEAMSchools/teamster: Delivered a substantial feature and reliability package, enabling richer analytics, automated data ingestion, and stronger governance. Key work spanned data model enhancements for demographics, cross-survey analytics, integration work, scheduling, security, and multiple reliability fixes that reduce operational risk and improve reporting accuracy. Business impact includes improved data quality, faster, more trustworthy insights, and lower maintenance overhead.
March 2025
12 Commits • 4 Features
Mar 1, 2025March 2025 monthly performance for TEAMSchools/teamster focused on delivering data accuracy, streamlined access controls, and maintainable code quality. Key features delivered include Tableau Usage Report Enhancements and Data Enrichment, Stipend and Bonus AppRoster Access Control and Simplification, a new Primary Status Flag in the schema, and comprehensive Maintenance and Cleanup (Refactor and Lint). These efforts improved reporting fidelity, reduced operational friction in roster handling, and strengthened data governance while setting a cleaner foundation for future enhancements.
12 Commits • 4 Features
Mar 1, 2025March 2025 monthly performance for TEAMSchools/teamster focused on delivering data accuracy, streamlined access controls, and maintainable code quality. Key features delivered include Tableau Usage Report Enhancements and Data Enrichment, Stipend and Bonus AppRoster Access Control and Simplification, a new Primary Status Flag in the schema, and comprehensive Maintenance and Cleanup (Refactor and Lint). These efforts improved reporting fidelity, reduced operational friction in roster handling, and strengthened data governance while setting a cleaner foundation for future enhancements.
March 2025
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 — TEAMSchools/teamster: Tableau Usage Analytics Improvements. No major bugs fixed this month. Delivered SQL refactor to improve data consistency and URL generation, standardized user names and timestamps, and dynamic view URL construction to enhance dashboard reliability. These changes boost data quality, reduce dashboard maintenance, and accelerate data-driven decision making.
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 — TEAMSchools/teamster: Tableau Usage Analytics Improvements. No major bugs fixed this month. Delivered SQL refactor to improve data consistency and URL generation, standardized user names and timestamps, and dynamic view URL construction to enhance dashboard reliability. These changes boost data quality, reduce dashboard maintenance, and accelerate data-driven decision making.
Activity
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Quality Metrics
Correctness90.6%
Maintainability87.6%
Architecture86.0%
Performance84.0%
AI Usage27.8%
Skills & Technologies
Programming Languages
BashJSONJavaScriptMarkdownPythonSQLYAML
Technical Skills
API DevelopmentAPI IntegrationAPI designAPI developmentAPI integrationBackend DevelopmentBigQueryCI/CD ConfigurationCloud ComputingCloud DeploymentConfiguration ManagementCubeCube APICube CloudCube.js
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