Senior Data Engineer

Role: Senior Data Engineer

Join CareScout’s data and machine learning organization to build the pipelines, models, and infrastructure that power analytics, ML, and operational data needs.

What you’ll do

• Data pipeline engineering: Design, build, and maintain scalable ETL/ELT pipelines using Spark, Python, SQL, and Databricks.
• Implement batch and streaming ingestion frameworks and ensure SLAs, data quality standards, and production-grade reliability.
• Lakehouse modeling & architecture: Develop data models across raw, curated, and semantic layers using Delta Lake.
• Create dimensional models, star schemas, and domain-layer datasets for analytics and ML.
• Define standards for schema design, metadata, and lineage.
• Data quality & observability: Add data validation, anomaly detection, SLAs, and documentation.
• Build automated tests, monitoring, and alerting for data freshness, completeness, and accuracy.
• Collaborate on improving observability and operational tooling.
• Cross-functional collaboration: Work with analysts on KPIs and deliver curated datasets.
• Partner with ML/data science to build reusable feature pipelines and with platform teams to optimize compute, governance, and orchestration.

Requirements

• Strong engineering fundamentals.
• Deep knowledge of modern data architectures.
• Experience transforming complex datasets into high-quality, well-modeled information with business impact.
• Comfortable owning end-to-end pipelines, improving data quality and reliability, and raising engineering excellence.

Nice-to-haves / inferred traits

• Experience mentoring others and building repeatable engineering processes.
• Familiarity with end-to-end production data reliability (tests, monitoring, alerting, and documentation).