Delivery Centric is seeking an experienced Databricks Developer to engineer scalable, high-performance data solutions across enterprise platforms. This role drives end-to-end data pipeline development, optimizes Lakehouse frameworks, and ensures secure, reliable, and efficient data operations. You’ll collaborate closely with cross-functional teams to translate business requirements into resilient data architectures that accelerate decision-making and digital transformation.
Key Responsibilities
- Design, develop, and maintain robust data pipelines and Lakehouse solutions using Databricks and Delta architecture.
- Build scalable ETL workflows integrating Databricks with orchestration tools and enterprise data ecosystems.
- Develop high-performance Spark-based transformations using DataFrame APIs, Spark SQL, and Python/Scala.
- Leverage Databricks-native capabilities including Workflows, Delta Live Tables, and Unity Catalog for governance and automation.
- Configure and optimize Databricks workspaces, clusters, and jobs for performance, cost efficiency, and operational reliability.
- Implement data security, lineage, audit, and monitoring practices aligned with enterprise governance standards.
- Develop and maintain streaming solutions using Spark Structured Streaming and Autoloader with diverse ingestion platforms.
- Contribute to the design of conceptual, logical, and physical data models supporting analytical and operational workloads.
- Stay current with Databricks best practices, emerging capabilities, and modern data engineering trends.
Qualifications
- Minimum 5+ years in IT with 3+ years hands-on in Databricks design, development, and operational support.
- Proven expertise in Lakehouse Architecture including Delta Tables, Schema Evolution, ACID, versioning, and history tracking.
- Strong command of Spark ecosystem—DataFrame API, Spark SQL, Python/Scala programming, and SQL proficiency.
- Experience integrating Databricks with ETL/orchestration tools for enterprise-scale data operations.
- Hands-on exposure to Databricks Workflows, Delta Live Tables, Unity Catalog, and platform-native automation.
- Strong knowledge of cluster configuration, performance tuning, cost management, data security, and monitoring.
- Experience delivering streaming pipelines using Structured Streaming and Autoloader integrations.
- Understanding of data modeling frameworks across conceptual, logical, and physical layers.
- Bonus: Exposure to AI/GenAI workloads and Databricks/Cloud certifications (associate or professional level).
Join a high-performing data and cloud engineering practice where innovation, automation, and enterprise-scale delivery drive measurable business impact. You’ll work with modern platforms, proven frameworks, and a team committed to excellence in data engineering, analytics, and cloud transformation.