Senior Data Engineer
Summary
Senior Data Engineer builds and maintains scalable healthcare data pipelines using Azure Databricks, PySpark, and Medallion Architecture, while mentoring junior engineers and ensuring production-grade data quality.
Cloud Raptor is a global cloud technology and consulting firm delivering Cloud, Data, Analytics, and AI solutions across Australia, India, Canada, UAE, the UK, and the Philippines. We cultivate an inclusive, multicultural workplace that values diversity, equitable opportunities, and the well‑being of our people. Our culture emphasizes collaboration, professional growth, and a healthy work‑life balance.
Position Summary
We are seeking a Senior Data Engineer to join our Manila office to design, build, and maintain a modern data platform for healthcare clients. This is a hands‑on technical role with leadership responsibilities: you will guide two junior data engineers, own the team’s technical deliverables, and collaborate closely with business and analytics stakeholders to ensure high‑quality, production‑grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Azure Databricks, PySpark, Python, SQL, Delta Lake, Azure Data Factory (ADF), and ADLS Gen2.
- Implement Medallion Architecture (Bronze, Silver, Gold) including incremental processing, slowly changing dimensions (SCD), and robust data validation.
- Perform unit testing, data validation, and reconciliation of developed pipelines.
- Ensure data quality through validation, logging, monitoring, and automated checks.
- Optimize Apache Spark workloads for performance, reliability, and cost efficiency.
- Implement data governance, security, and access control using Unity Catalog.
- Manage Databricks Workflows, support production deployments and troubleshooting, and maintain CI/CD pipelines via Azure DevOps.
- Lead, mentor, and conduct code reviews for two junior data engineers; plan tasks and uphold engineering standards.
- Take ownership of delivery quality, adhere to best practices, and liaise with stakeholders to align technical work with business objectives.
Required Qualifications
- 7+ years of professional data engineering experience with demonstrable, hands‑on expertise in Azure Databricks, PySpark, Python, and SQL.
- Strong experience with Apache Spark, Delta Lake, Azure Data Factory, ADLS Gen2, and Unity Catalog.
- Proven understanding of Medallion Architecture, incremental processing strategies, SCDs, data modeling, and Spark performance tuning.
- Experience with Git, Azure DevOps, CI/CD processes, and production support.
- Prior experience leading or mentoring data engineers is essential.
- Exposure to Power BI, Databricks AI features, or healthcare/insurance data is advantageous.
Personal Attributes
We seek a candidate who:
- Demonstrates accountability and follows through on commitments.
- Leads by example and actively mentors junior colleagues.
- Communicates clearly with both technical and non‑technical stakeholders.
- Applies a solution‑focused, collaborative approach to problem solving.
- Thrives in a multicultural, distributed team environment.
- Values quality, continuous learning, and knowledge sharing.
What We Offer
At Cloud Raptor, we offer competitive compensation and attractive employee perks, along with a flexible and inclusive work environment that promotes healthy work-life balance, continuous learning, career growth, and equal opportunities.