Senior Data Engineer — Cloud Pipelines & Governance

Role:
Senior Data Engineer

Remote Work: INDIA

Location:

Hyderabad / Noida, INDIA

* Only Consultants local to INDIA are eligible.

* No visa Sponsorship

• Design, develop, and maintain scalable data pipelines using Python, PySpark, and other modern programming languages to support both batch and streaming workloads.
• Build and optimize data processing frameworks on cloud platforms such as Databricks or Snowflake, ensuring performance, reliability, and cost efficiency.
• Design and implement robust data models, including transactional (OLTP) and dimensional (OLAP) schemas, to support analytics, reporting, and application integration.
• Develop high quality SQL code including complex queries, stored procedures, and views, with a focus on performance tuning and efficient data access patterns.
• Create and manage workflow orchestration using Apache Airflow or similar tools, ensuring reliable scheduling, dependency management, and monitoring.
• Implement and enforce data governance and metadata standards through tools such as Microsoft Purview, including data lineage, classification, cataloging, and security policies.
• Build automated data quality and validation frameworks to ensure accuracy, completeness, and reliability of production datasets.
• Collaborate with cross functional teams including data architects, analysts, scientists, and business stakeholders to understand requirements and deliver scalable, well designed data solutions.
• Lead technical design sessions and code reviews, promoting engineering best practices, reusability, and maintainability.
• Support cloud infrastructure and Dev Ops practices, including CI/CD pipelines, version control, testing automation, and environment management.
• Monitor and troubleshoot production data pipelines, proactively addressing issues, performance bottlenecks, and system failures.
• Contribute to the evolution of the enterprise data platform, recommending tools, frameworks, and architectures to improve scalability and efficiency.

• 5+ years of experience in data engineering, software engineering, or similar disciplines.
• Hands‑on experience with Databricks or Snowflake.
• Experience with orchestration tools such as Apache Airflow.
• Experience working with cloud ecosystems (Azure preferred; AWS/GCP acceptable).
• Advanced SQL skills and experience with OLTP and OLAP data modeling.
• Solid understanding of modern data warehousing, data lake, and ELT/ETL design patterns.
• Familiarity with data governance tools, especially Microsoft Purview.
• Solid programming expertise in Python, PySpark, or similar languages.

• Healthcare industry experience, including claims, clinical, FHIR, HL7, or provider data.
• Experience with containerization (Docker, Kubernetes) for data workloads.
• Experience supporting machine learning workflows or analytical data science pipelines.
• Knowledge of distributed computing concepts and performance tuning.