Senior Data Engineer

Responsibilities:

• Production APIs: Serve analytics and ML outputs across GCC deployments.
• ETL/ELT Pipelines: Feed workloads like supply chain forecasting, claims adjudication, and population health.
• Predictive Models: Build statistical/ML models for commodity flows, payer analytics, health indicators.
• Collaboration Translate clinical/operational questions into measurable data problems.
• Model Lifecycle: Monitor, retrain, and ensure data quality frameworks.
• Architecture Input: Extend lakehouse stack (Iceberg, ClickHouse, Parquet, Dagster, lakeFS, dbt).
• Coding Standards: Write clean, production-grade Python/SQL code.

Requirements:

• Experience: 6-9 years split between data science + backend/data engineering.
• Core Tech: Python (Pandas, NumPy, scikit-learn, SQLAlchemy, FastAPI), SQL, columnar DBs (ClickHouse preferred).
• Deployment: Proven track record of shipping and maintaining ML models in production.
• Event-Driven Systems: Kafka familiarity is a plus.
• Transformation Tools: dbt or equivalent; knowledge of medallion/lakehouse patterns.
• Domain Knowledge: FHIR, claims, supply chain, logistics (bonus differentiator).
• Context: Comfort in B2G environments with sovereignty, auditability, compliance.

Skills

ELT, ETL, backend, data engineering, python, sql