Databricks Data Engineer with DevOps Skills

We are looking for an experienced Databricks Data Engineer with strong DevOps expertise to join our data engineering team. The ideal candidate will design, build, and optimize large-scale pipelines on the Databricks Lakehouse Platform on AWS, while driving automated CI / CD and deployment practices. This role requires strong skills in PySpark, SQL, AWS cloud services, and modern DevOps tooling. You will collaborate closely with cross-functional teams to deliver scalable, secure, and high-performance data solutions.

Must Demonstrate (Critical Skills & Architectural Competencies)

• Designing and implementing Databricks-based Lakehouse architectures on AWS
• Clear separation of compute vs. serving layers
• Ability to design low-latency data / API access strategies (beyond Spark-only patterns)
• Strong understanding of caching strategies for performance and cost optimization
• Data partitioning, storage optimization, and file layout strategy
• Ability to handle multi-terabyte structured or time-series datasets
• Skill in requirement probing, identifying what matters architecturally
• A player-coach mindset : hands-on engineering + technical leadership

Key Responsibilities

1. Data Pipeline Development

2. DevOps & CI / CD

3. Collaboration & Business Support

4. Performance & Optimization

5. Governance & Security

Technical Skills

Delta Lake

S3

Git / GitLab

Preferred Experience

Certifications (Optional)

AWS Data Engineer or AWS Solutions Architect certification