Data Engineer

• Stand up a scalable Databricks lakehouse to ingest, model, and serve business operations data (finance, resourcing, project delivery, CRM, marketing, and time tracking)
• Design and maintain automated ELT/ETL pipelines that move data from SaaS tools, databases, and files into bronze/silver/gold layers
• Build the core semantic layer (cleaned, conformed, documented tables) that powers self-serve BI and executive dashboards
• Replace legacy/manual engagement and utilization reports with scheduled, monitored jobs and SLAs
• Partner with Business Operations, Finance, and People Operations leaders to define source-of-truth metrics (e.g., revenue, margin, utilization, velocity, pipeline, engagement health)
• Lay groundwork for AI use cases (RAG over operational data, agentic processes, querying company data) by implementing robust lineage, metadata, and access controls
• Architecture & Modeling: Design lakehouse architecture, dimensional/medallion models, and data contracts across systems
• Pipeline Automation: Implement CI/CD for data (branching, PRs, jobs, environments), with observability and reproducibility
• Data Governance: Enforce PII/PHI handling, role-based access, auditability, and retention aligned to healthcare-adjacent standards
• Enablement: Document datasets, publish a data catalog, and enable self-serve usage via BI and SQL
• Reporting Modernization: Decommission manual spreadsheets and one-off extracts
• consolidate to certified, scheduled outputs
• AI Readiness: Capture lineage/metadata and vector-friendly document stores to support future ML and RAG initiatives

• 2+ years in data engineering or analytics engineering, including building production data pipelines at scale
• Expert with Databricks (Delta Lake, SQL, PySpark) and cloud data platforms (AWS or Azure)
• Proficient with dbt and/or Delta Live Tables
• strong SQL and data modeling fundamentals
• Experience orchestrating jobs (Airflow, Databricks Workflows, or equivalent)
• Comfortable with PowerBI and semantic modeling for self-serve analytics
• Familiarity with data governance (RBAC/ABAC, secrets management, token-based auth) and healthcare-adjacent compliance (e.g., HIPAA concepts) is a plus
• Strong stakeholder skills. Can translate business needs into reliable data products and clear SLAs
• Databricks, Delta Lake, PySpark, SQL, dbt, REST/GraphQL APIs, Git/GitHub, Power BI/Tableau/Looker

Familiarity with data governance (RBAC/ABAC, secrets management, token-based auth) and healthcare-adjacent compliance (e.g., HIPAA concepts)