Data Architect

ALIS Software • Boston, MA

1d

About The Position

The Data Architect bridges enterprise data engineering and advanced analytics by ensuring data readiness, building scalable data products, engineering analytical datasets, and contributing to modeling and statistical analysis. The role defines enterprise architecture, data flows, and sourcing strategies across multiple systems, and guides development teams in building robust data management platforms on Databricks and AWS. It connects data ingestion and modeling to the delivery of KPIs and reports, with an emphasis on understanding life sciences data and how it relates to delivered metrics.

The position develops advanced ETL pipelines and uses AI frameworks and tools such as Databricks Genie, Claude, and Cursor AI. It also defines data models, semantic models, governance frameworks, data quality practices, and observability across platforms. The role collaborates across analytics and enterprise data engineering teams and supports high-performance dashboards, reporting, and analytical work.

Requirements

• The posting lists 12+ years of experience in its role summary and 18+ years of Data Engineering experience in the required qualifications.
• At least 7 years of strong Databricks experience.
• Experience in data architecture and enterprise architecture.
• Demonstrable data science capability.
• Experience with MDM platforms and master data management.
• Strong data governance, lineage, and catalog experience.
• 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.
• Experience managing agile scrums and projects for dashboarding and reporting.
• Team leadership and executive communication skills.
• Strong healthcare domain experience is emphasized in the posting.

Nice To Haves

• Strong data modeling experience.
• Experience with AI-led development tools and accelerators, including Databricks Genie, Claude, and Cursor AI.
• Experience with Tableau and data visualization tools.
• Working knowledge of life sciences or medical devices.
• Experience developing data and ETL accelerators.
• Atlan experience for data governance, lineage, and catalog capabilities.

Responsibilities

• Define data architecture and ETL flows for metrics and reporting.
• Apply Databricks best practices and implement relevant platform features, including AI/BI and Genie.
• Define data and semantic models for sourcing data from multiple source systems.
• Define data governance models, frameworks, and tools.
• Enable data quality frameworks and data observability across platforms.
• Build Databricks ETL pipelines from 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 reduce one-off extracts.
• Build automated, reusable ingestion and data quality frameworks.
• Implement automated 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.
• Optimize semantic layers and data models for high-performance dashboards and analytics.
• Document data lineage, transformation logic, refresh schedules, and operational dependencies.
• Guide development teams in building data management platforms on Databricks and AWS.
• Connect data ingestion and modeling to KPI and reporting delivery.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed