Senior Data Architect

11 hours ago

Boston, Massachusetts, United States TEK NINJAS Full time

Role: Data Architect (HR Data & Analytics)

Location: Boston, MA

Role Overview

The Data Architect – HR Data & Analytics will play a key role in designing and implementing the enterprise HR data architecture to support our clienty HR analytics, KPIs, and reporting initiatives.

This role involves translating complex business requirements into scalable, governed data solutions built on Snowflake and integrated with Workday and other HR systems. The ideal candidate will combine deep technical expertise with a strong understanding of HR data domains, ensuring data integrity, accessibility, and analytical value across the organization.

Key Responsibilities

Architecture & Modeling

  • Design and implement scalable, efficient Snowflake data models to support HR analytics, workforce planning, and KPI reporting.
  • Develop and optimize integrations between Workday, Snowflake, and downstream analytics platforms; ensure seamless, accurate data flow across systems.

Data Quality & Governance

  • Define and enforce data governance, quality, and metadata management standards to ensure data consistency and compliance.
  • Maintain comprehensive technical documentation and data dictionaries for warehouse structures, transformations, and integrations.

Engineering & Optimization

  • Monitor and tune ETL/ELT pipelines, ensuring high-performance data transformation and loading processes.
  • Participate in unit, integration, and regression testing to validate data pipelines and ensure data accuracy.

Collaboration & Support

  • Partner with HR, Data Engineering, and Analytics teams to translate business logic into reusable and governed data assets.
  • Support data analysis and troubleshooting across the full implementation and operational lifecycle of HR data solutions.

Required Experience & Skills

Technical Foundation

  • Proven experience architecting and implementing solutions on Snowflake or similar cloud data warehouse platforms.
  • Advanced SQL skills and hands-on experience with data transformation and pipeline optimization tools.
  • Strong understanding of ETL/ELT frameworks, data validation, and reconciliation techniques.
  • Experience with Python for data engineering, automation, or orchestration tasks.

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