Data Architect Databricks Architect

Job Title

Data Architect and Lead

Boston, MA or Remote

Department

Data & AI Engineering / Databricks/Analytics

Position Summary

Bridge enterprise data engineering and advanced analytics by ensuring data readiness, building scalable data products, engineering analytical datasets, and contributing directly to modeling and statistical analysis. Build advanced ETL pipelines and use AI frameworks like Claude, Cursor AI etc. Should be able to define enterprise architecture, data flows and sourcing data from multiple systems. Should be able to guide the development team in building robust data management platforms on Databricks and AWS. Tie the data ingestion and modelling to delivery of KPIs and reports. Should be able to understand the lifesciences domain and be able to translate and understand the underlying data and how it relates to the metrics being delivered.

Key Responsibilities

Define data architecture and ETL flows for metrics and reporting

Bring the best practices on Databricks and latest features including AI/BI, Genie etc and implement within the customer platform.

Define the data model and Semantic model for sourcing data from multiple source systems.

Define Data Governance models and frameworks and tools.

Enable the Data Quality frameworks and data observability across the platforms,

Build the Databricks ETL pipelines source to target for metrics reporting

Build and maintain pipelines and analytical datasets using enterprise standards and CI/CD practices.

Engineer reusable features and analytical datasets that eliminate one-off extracts. Build automated and reusable Ingestion and Data Quality frameworks.

Implement automated quality checks for completeness, freshness, referential integrity, and data drift.

Serve as the technical bridge between analytics pods and enterprise data engineering teams.

Contribute to modeling, statistical validation, experimentation, and hypothesis testing activities.

Optimize semantic layers and data models for high-performance dashboards and analytics.

Document lineage, transformation logic, refresh schedules, and operational dependencies.

Required Qualifications

18+ years of Data Engineering experience with demonstrable Data Science capability.

Experience in Data architecture and enterprise architecture.

Strong Data Modeling experience preferred.

Strong expertise in AI led development Databricks Genie, Claude, Cursor AI etc.

Experience in MDM platforms and Master data management.

Strong Data Governance, Lineage and catalog experience preferably Atlan.

Expert skills in Databricks Need strong experience of atleast 7 + years.

Strong Skills in AI tools and accelerators

Experience preferred on Tableau and data visualization tools.

Working knowledge on lifescience, medical devices domain preferable.

Experience in Data and ETL accelerators development

Expert SQL and Python skills.

Production experience with modern cloud data platforms and orchestration solutions.

Hands-on experience with dbt or equivalent transformation tooling.

Strong knowledge of ETL/ELT, data modeling, analytics engineering, and statistical methods.

Excellent Communication skills and team leadership experience.

Should have managed agile scrums and projects for dashboarding and reporting.

Team Leadership and executive communication skills are a must.