Data Engineer / Data Modeler
About The RoleWe're looking for a Senior Data Engineer / Data Modeler who can both build scalable data pipelines and design the data models that make that data usable for BI, analytics, and GenAI use cases. You'll work directly with Fortune 500 clients across industries in small, high-ownership pods that blend consulting rigor with hands-on engineering. This is a fully remote role.Key ResponsibilitiesDesign and build scalable batch/streaming pipelines to ingest, transform, and deliver data into cloud platforms. Design conceptual, logical, and physical data models (dimensional, relational, semantic) for BI, analytics, and AI consumption. Translate business requirements into star/snowflake schemas and ER diagrams with architects and governance teams. Build and maintain data warehouses/lakehouses on Azure, AWS, GCP, or Snowflake. Implement data quality, validation, and reconciliation frameworks. Enforce data modeling standards and documentation practices. Tune pipeline and query performance for large-scale datasets. Structure data for ML/GenAI use cases in collaboration with data science teams. Work across the full SDLC with strong engineering practices (version control, CI/CD, code review). Present and defend data model designs to technical and business stakeholders, including mentoring junior engineers. Required QualificationsBachelor's in Computer Science, Engineering, or related field (Master's preferred). 7-10 years in data engineering, including 4+ years of hands-on data modeling (relational and dimensional). Healthcare domain experience is required. Experience in a consulting or client-facing delivery environment is a plus. Required Technical SkillsLanguages: Advanced SQL (T-SQL/PL-SQL), PythonData Modeling: Dimensional modeling, star/snowflake schemas, ER diagramming, data warehouse designCloud: Azure (ADF, Synapse, Databricks) and/or AWS (Glue, Redshift) and/or GCP (BigQuery)Big Data: Spark, KafkaPlatforms: Snowflake, DatabricksETL/ELT: ADF, SSIS, dbtEngineering: Git, Terraform, Docker, CI/CDPreferred SkillsSemantic layer design for self-service and AI-ready analyticsExposure to feature stores or vector databases for RAG/LLM pipelinesData governance/catalog tools (Purview, Collibra, Atlas)BI tools (Power BI, Tableau) from a modeling standpointGood-to-Have SkillsExposure to Azure OpenAI, AWS Bedrock, or Vertex AIMLOps familiarityBash/PowerShell scriptingAPI-based/event-driven data integrationSoft SkillsStrong stakeholder communication and ability to simplify complex modelsOwnership mindset and comfort with ambiguityFirst-principles problem-solvingDocumentation discipline and attention to detailPreferred CertificationsMicrosoft Azure Data Engineer Associate (DP-203)SnowPro Core/Advanced: Data EngineerDatabricks Certified Data EngineerGoogle Professional Data Engineer