Key Responsibilities
- Lead and manage teams of data engineers, analysts, and developers to deliver high-quality, production-ready data platforms.
- Own the design, development, and maintenance of data pipelines, data lakes, and data warehouses.
- Ensure data availability, performance, reliability, scalability, and cost efficiency across platforms.
- Translate business requirements into robust technical architectures and implementation plans.
- Define and enforce data governance, security, and compliance standards.
- Drive continuous improvement of data engineering processes, frameworks, and tooling.
- Mentor, guide, and develop team members through technical leadership and career planning.
- Manage project delivery, resource planning, timelines, and execution milestones.
- Partner with BI, Product, IT, and Cloud teams to enable organization-wide data-driven decision making.
- Evaluate and adopt emerging technologies and best practices in cloud and data engineering ecosystems.
Required Skills & Qualifications
- Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related fields.
- 11+ years of experience in data engineering or related domains, including 3+ years in a lead or people-management role.
- Strong expertise in SQL, data modeling, and ETL/ELT design.
- Hands-on experience with Azure cloud platforms, including Databricks and Snowflake.
- Proficiency with modern data frameworks and tools such as Apache Spark, Kafka, Airflow.
- Solid knowledge of data governance, security, and compliance frameworks (GDPR, HIPAA, etc.).
- Proven leadership, communication, and stakeholder management capabilities.
- Demonstrated ability to manage complex priorities in high-growth, fast-paced environments.
- Strong hands-on experience in orchestrating Databricks pipelines, automated workflows, and job scheduling.
- Expertise with Databricks Unity Catalog, Hive Metastore, and building Databricks dashboards for monitoring and visualization.
- Working experience with Azure Functions for serverless and event-driven data workflows.
- Proven implementation of Medallion Architecture (BronzeSilverGold) for scalable ingestion, transformation, and delivery.
- Experience building end-to-end data pipelines on Azure + Databricks environments.
