Senior / Lead Data Engineer - Healthcare Analytics (GCP)

Job Title: Senior / Lead Data Engineer Healthcare Analytics (GCP)

Experience: 810+ Years

Location: Remote

Time: 5:30 PM IST to 2:30 AM IST

Domain: Healthcare Data & Analytics

Primary Cloud: Google Cloud Platform (GCP)

Job Summary

We are seeking a highly experienced Senior / Lead Data Engineer with deep hands-on expertise in building scalable data platforms on Google Cloud Platform (GCP). The ideal candidate will have strong experience in healthcare data modeling, preferably with EPIC EMRsourced data, and a proven ability to design analytics-ready data models that support enterprise reporting, BI, and downstream analytics use cases. This role requires strong proficiency in SQL, Python, data modeling, and analytics enablement, with close collaboration across data, analytics, and business stakeholders in a regulated healthcare environment.

Key Responsibilities

Data Engineering & Cloud Platform (GCP)

? Design, build, and maintain scalable, reliable data pipelines on GCP using services such as BigQuery, Dataflow, Composer (Airflow), Cloud Storage, and related tools.

? Implement batch and nearreal-time ingestion and transformation workflows for large healthcare datasets.

? Ensure high data quality, reliability, and performance across the data platform.

Healthcare Data Modeling (EPIC EMR)

? Design and implement analytics-ready data models for healthcare data sourced from EPIC EMR systems.

? Apply dimensional modeling techniques (fact/dimension tables, star/snowflake schemas) to support clinical, operational, and financial reporting.

? Incorporate healthcare data standards and ensure compliance with HIPAA, PHI/PII handling, and data anonymization requirements.

? Partner with analytics and business teams to translate reporting and metric requirements into robust data models.

Data Analysis & Analytics Readiness

? Profile, analyze, and validate raw healthcare data to ensure accuracy and consistency before exposure to analytics layers.

? Define business metrics, KPIs, and aggregation logic aligned with clinical and operational use cases.

? Build curated datasets and semantic layers optimized for BI consumption and self-service analytics.

SQL (Advanced Analytics & Optimization)

? Write and optimize complex SQL queries, including CTEs, window functions, nested queries, and large-scale joins.

? Tune queries and data models for performance and cost efficiency on large datasets in BigQuery or similar warehouses.

? Establish SQL best practices for maintainability and scalability.

Python (Data Engineering & Transformation)

? Use Python for data transformation logic, validation, orchestration, and automation within data pipelines.

? Integrate Python-based transformations with SQL-driven ELT workflows.

? Develop reusable, well-documented data engineering utilities and frameworks.

BI & Data Visualization Enablement

? Support BI tools such as Looker, Power BI, or Tableau by designing robust underlying data models.

? Understand LookML concepts (dimensions, measures, explores) and ensure alignment with warehouse schemas.

? Partner with analytics teams to validate dashboards and ensure accurate, trusted insights.

Required Qualifications

? 8-10+ years of hands-on experience in Data Engineering, preferably in healthcare or regulated industries.

? Strong experience with Google Cloud Platform (GCP) data services (BigQuery, Dataflow, Composer/Airflow).

? Proven hands-on experience in healthcare data modeling, ideally with EPIC EMR or similar EMR systems.

? Expert-level SQL skills for analytics, optimization, and large-scale datasets.

? Strong Python experience for data transformation and pipeline development.

? Solid understanding of dimensional data modeling and analytics-ready design patterns.

? Experience enabling BI and analytics use cases through well-designed data models.

? Strong understanding of data governance, data quality, and compliance (HIPAA, PHI/PII).

Nice to Have

? Direct experience with the EPIC Analytics Ecosystem (Caboodle, Clarity, or downstream analytics layers).

? Experience with DBT or similar modern data modeling frameworks.

? Exposure to Looker semantic modeling (LookML).

? Experience working in agile, cross-functional healthcare data teams.

What Were Looking For

? A hands-on data engineer with end-to-end ownership of data modeling and analytics enablement, including BI migrations from Tableau to Looker and Power BI.

? Strong problem-solving and analytical mindset with attention to data quality and performance.

? Ability to communicate complex data concepts clearly to technical and non-technical stakeholders.

? A candidate who thrives in complex healthcare data environments and delivers production-grade solutions.