Posted on: 25/06/2026
Key Responsibilities :
Architecture & Design :
- Lead the design and implementation of end-to-end Medallion Architecture (Bronze, Silver, Gold layers) using Delta Lake.
- Design scalable and maintainable data solutions aligned with enterprise standards.
Pipeline Development & Optimization :
- Build scalable batch and real-time streaming pipelines using PySpark, SQL, and Delta Live Tables (DLT).
- Perform advanced performance tuning including Z-Ordering, Liquid Clustering, partitioning, and Spark UI debugging to reduce compute costs and improve latency.
Data Governance & Security :
- Implement and manage enterprise-grade security and data lineage using Unity Catalog.
- Establish data governance frameworks and best practices across the organization.
Orchestration & DevOps :
- Manage complex workflows using Databricks Workflows or Apache Airflow.
- Implement CI/CD using Databricks Asset Bundles (DABs) and Git integration.
Migration & Integration :
- Lead migrations from legacy systems (Hadoop, On-prem SQL, SAP HANA) to the Databricks Lakehouse.
Technical Leadership & Mentoring :
- Act as the primary point of contact for Databricks architecture decisions.
- Conduct code reviews and mentor junior staff.
- Participate in the development of standards, processes, and frameworks to enhance overall data integration capabilities.
- Continuously stay updated with the latest trends and technologies in the data integration and cloud data platform space.
Core Competencies Required :
Databricks & Platform Expertise :
- Expert-level knowledge of Databricks (Photon engine, Unity Catalog, Serverless SQL, Lakeflow).
- Deep understanding of Delta Lake ACID transactions and Medallion Architecture patterns.
Programming & Data Processing :
- Mastery of Python/PySpark and Advanced SQL.
- Deep understanding of Apache Spark internals and Structured Streaming.
- Scala knowledge is a plus.
Cloud & Infrastructure :
- Extensive experience with at least one major cloud platform (Azure, AWS, or GCP).
- Proficiency with cloud-native storage solutions (ADLS Gen2, S3, GCS).
- Proficiency with Terraform and infrastructure-as-code practices.
DevOps & CI/CD :
- Proficiency with GitHub Actions or Azure DevOps.
- Experience implementing CI/CD pipelines for data engineering workflows.
Data Engineering Specialization :
- Expertise in ELT (Extract, Load, Transform) patterns and reporting frameworks.
- Strong understanding of data ecosystem design and data governance.
- Experience with performance optimization and cost management in cloud data platforms.
Soft Skills :
- Strong communication skills with the ability to explain complex technical concepts to non-technical business leaders.
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1648483