Lead Data Engineer

We are looking for a Data Engineer with 6–12 years of experience in building and supporting scalable data engineering solutions across Azure and Big Data platforms. The ideal candidate should have strong hands-on experience with Azure Databricks, PySpark, Hadoop, Talend, Delta Lake, and Azure Data Factory (ADF).

The role will involve developing, integrating, and optimizing data pipelines that support analytics, reporting, and AI/ML initiatives, while working closely with data architects, engineers, and business stakeholders.

Key Responsibilities

• Develop and maintain scalable data pipelines using Azure Databricks and PySpark.
• Build data transformation and processing solutions using Delta Lake and Lakehouse architecture.
• Develop and optimize ETL/ELT pipelines using Talend for large-scale data ingestion and transformation.
• Work with Hadoop ecosystem technologies for distributed data processing and storage.
• Integrate data from multiple sources including databases, APIs, files, and streaming platforms.
• Build and manage data orchestration workflows using Azure Data Factory (ADF).
• Optimize Spark jobs, Databricks clusters, and data pipelines for performance and cost efficiency.
• Implement data quality, validation, security, and governance practices.
• Collaborate with architects, business stakeholders, and data teams to understand requirements and deliver technical solutions.
• Participate in code reviews, technical discussions, and implementation of engineering best practices.
• Work with DevOps teams on CI/CD and deployment automation for data engineering solutions.
• Troubleshoot and resolve data pipeline and production issues.

Must-Have Skills

• 6–12 years of experience in Data Engineering / Big Data Engineering.
• Strong hands-on experience with Azure Databricks and PySpark.
• Strong experience with Hadoop and its ecosystem.
• Hands-on experience with Talend for ETL/data integration.
• Good experience with Delta Lake / Lakehouse architecture.
• Strong experience with Azure Data Factory (ADF).
• Strong SQL and data transformation skills.
• Experience working with large-scale datasets and distributed data processing.
• Understanding of cloud-based data engineering and data integration concepts.
• Exposure to CI/CD and DevOps practices.