Data Engineer (Healthcare Data & SQL Expert)
5 - 7 yrs
₹10L - ₹25L / yr
Remote only
Skills
PythonSQL
RDMS
ETL
Database Design
Advanced SQL
ETL/ELT Pipelines
HIPAA
FHIR
HL7
EMR/EHR
Cloud
Sr. DE / Data Engineer (Healthcare Data & SQL Expert)
Experience Level: 5–7 Years
Focus: Database Design, Advanced SQL, ETL/ELT Pipelines, and Healthcare Interoperability.
Summary
We are looking for a highly skilled Senior Data Engineer to join our healthcare data team. This role is perfect for a technical powerhouse who excels at building robust data pipelines and deeply understands database internals. You will be responsible for designing schemas, writing complex stored procedures, and optimizing SQL performance to handle clinical and claims data at scale. You will bridge the gap between raw data ingestion and high-performance analytics, ensuring all solutions meet HIPAA and FHIR standards.
What You’ll Do
1. Advanced SQL & Database Development
- Schema Design: Design and implement relational schemas (MSSQL, PostgreSQL, Oracle) ensuring data integrity through constraints, triggers, and normalized structures.
- Programmability: Write and maintain sophisticated Stored Procedures, Functions, and Views to handle complex business logic within the database layer.
- Performance Tuning: Own query optimization. You should be the expert in reading EXPLAIN/ANALYZE plans, implementing advanced indexing strategies (Clustered, Non-Clustered, Columnstore), and managing partitioning.
- Data Modeling: Build and manage dimensional models (Star/Snowflake) and implement Slowly Changing Dimensions (SCD Types 1, 2, and 4).
- Getty Images
2. Data Engineering & Ingestion
- Pipeline Development: Build and operate scalable ETL/ELT pipelines using Python and SQL to ingest data from EHRs, REST APIs, and flat files.
- Orchestration: Use Apache Airflow to schedule jobs, manage dependencies, and implement robust retry/alerting logic.
- API Integration: Develop Python-based ingestion frameworks that handle OAuth, pagination, and throttling for third-party healthcare data partners.
3. Healthcare Interoperability & Compliance
- Standards: Map complex clinical data to HL7 FHIR resources and curated analytic layers.
- Security: Implement "Privacy by Design" by enforcing HIPAA safeguards, including encryption at rest, access controls, and PII/PHI de-identification.
4. Operational Excellence
- CI/CD: Use GitHub and automated pipelines to deploy database changes and data code.
- Observability: Implement data quality tests (using tools like dbt or custom Python/SQL checks) to monitor freshness and accuracy.
What You’ll Bring
- Experience: 5–7 years of professional data engineering experience, with a heavy emphasis on backend database development.
- The SQL Expert Toolkit:
- Expert SQL: Window functions, CTEs, recursive queries, and set-based transformations.
- DB Internals: Deep knowledge of MSSQL, PostgreSQL, or Oracle. You should understand how the engine stores and retrieves data.
- Optimization: Proven track record of turning "slow" queries into high-performance assets via indexing and refactoring.
- The Engineering Toolkit:
- Python: Intermediate to advanced (Pandas/Polars, Requests, SQLAlchemy, or PySpark).
- Orchestration: Practical experience with Airflow (or Prefect/Dagster).
- Legacy/Cloud mix: Proficiency in SSIS/SSMA or PowerShell is a plus for migrating legacy workloads to modern platforms.
- The Domain Knowledge: Familiarity with FHIR/HL7 and an understanding of the importance of data governance in a regulated environment.
Technical "Must-Haves" for the Interview
- Ability to whiteboard a complex Database Schema from scratch.
- Ability to debug a long-running SQL query and explain the IO/CPU trade-offs of different index types.
- Experience handling JSON/BSON data types within a relational database context.
Nice to Have
- Experience with NoSQL systems like MongoDB or Elasticsearch.
- Cloud experience (Azure, AWS, or GCP) specifically regarding managed SQL services.
- Knowledge of dbt (data build tool) for managing transformations in the warehouse.
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About Mango Sciences
Founded :
2019
Type :
Product
Size :
20-100
Stage :
Raised funding
About
N/A
Company social profiles
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