Lead Data Engineer

Role Overview

We are seeking a skilled Data Engineer to design, build, and optimize Azure-based data pipelines and lakehouse solutions. The ideal candidate will deliver secure, reliable datasets with strong governance, automation, and documentation while collaborating across teams in an Agile environment. This role requires strong expertise in Databricks, Python, Spark, data pipelines, and Azure ecosystem, along with a focus on performance, scalability, and data quality.

Key Responsibilities

• Design and develop scalable data pipelines using Azure and Databricks
• Build and maintain ETL/ELT workflows from diverse data sources
• Experience with Unity Catalog migration and data governance.
• Develop data transformations using Python, Spark, and Pandas
• Implement Delta Lake and Medallion architecture (Bronze/Silver/Gold layers)
• Manage data storage using Azure Data Lake Storage (ADLS)
• Design and optimize SQL queries and data models (star/dimensional schema)
• Implement CI/CD pipelines for data workflows using Azure DevOps or GitHub
• Ensure data quality, validation, monitoring, and observability
• Implement secure data access using Azure Entra ID (SSO/RBAC)
• Maintain clear documentation for pipelines and data contracts
• Participate in Agile ceremonies, code reviews, and team collaboration
• Support and mentor junior team members

Required Skills & Experience

• 8+ years of experience in Data Engineering
• Strong experience with Azure Databricks (Python, Spark, Pandas)
• Experience with Azure Data Factory (ADF) for orchestration
• Hands-on experience with Delta Lake and Medallion architecture
• Strong knowledge of Azure Data Lake Storage (ADLS)
• Experience with Unity Catalog migration and data governance
• Strong proficiency in SQL and performance optimization
• Experience in ETL/ELT and data modeling (star/dimensional schema)
• Experience with CI/CD tools (Azure DevOps or GitHub Enterprise)
• Understanding of Azure Entra ID for security and access control
• Experience in data validation, testing, and monitoring pipelines
• Familiarity with Agile/Scrum methodologies (Jira/Confluence)
• Strong communication, documentation, and collaboration skills

Preferred Experience :

• Experience with Databricks DevOps (cluster configuration, secrets management)
• Experience with Azure Functions (Python or C#)
• Exposure to Synapse SQL pools, dbt, or Delta Live Tables
• Experience in Financial Services domain
• Ability to work independently and contribute to team outcomes
• Strong focus on secure, production-grade data solutions
• Commitment to data reliability, performance, and governance
• Continuous learning mindset and adaptability

Responsible use of Generative AI tools with validation and guardrails