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Data Pipeline Architect
3 weeks ago
A highly skilled Lead Data Engineer is needed to design, develop, and optimize data pipelines using Azure and Databricks.
Key Responsibilities:
- Design, develop, and optimize data pipelines using Azure and Databricks.
- Work hands-on with Databricks Asset Bundles (DABs) for CI/CD and environment management.
- Build and manage scalable ELT/ETL workflows with Databricks, Delta Lake, ADF, and other Azure services.
- Continuously adopt and apply new Databricks features to accelerate delivery.
- Optimize Spark, SQL, and Python code for performance and scalability.
- Apply software engineering best practices (e.g., TDD, CI/CD, modular design, code reviews) to ensure a robust, maintainable, and strategic data ecosystem.
- Mentor team members to improve overall team productivity and technical capability.
Required Skills & Experience:
- 8+ years in Data Engineering with at least 5 years hands-on in Azure & Databricks.
- Strong expertise in:
- Databricks (Delta Lake, Databricks SQL, Workflows, Databricks Asset Bundles, MLflow basics, unity catalog)
- Azure Data Services (ADF, Azure Synapse, Azure Data Lake, Azure SQL)
- Python, SQL, Spark (with proven performance optimization skills)
- Strong knowledge of modern data architectures (Lakehouse, governance).
- Track record of efficient delivery and helping teams accelerate execution.
Benefits:
- Ability to work in a fast-paced environment with quick turnaround expectations.
- Team-first approach – drives collective improvement and efficiency.
- Highly motivated, proactive, and results-oriented.
Preferred Skills:
- Experience with AI-driven development tools to accelerate coding and improve productivity.
- Exposure to Generative AI in Databricks – good to have.
Requirements:
- Must have 5–6 hours daily overlap with USA team (EST time zone) for collaboration.
