Job Description
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).
nThe 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.
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nKey Responsibilities
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- Develop and maintain scalable data pipelines using Azure Databricks and PySpark.n
- Build data transformation and processing solutions using Delta Lake and Lakehouse architecture.n
- Develop and optimize ETL/ELT pipelines using Talend for large-scale data ingestion and transformation.n
- Work with Hadoop ecosystem technologies for distributed data processing and storage.n
- Integrate data from multiple sources including databases, APIs, files, and streaming platforms.n




- Build and manage data orchestration workflows using Azure Data Factory (ADF).n
- Optimize Spark jobs, Databricks clusters, and data pipelines for performance and cost efficiency.n
- Implement data quality, validation, security, and governance practices.n
- Collaborate with architects, business stakeholders, and data teams to understand requirements and deliver technical solutions.n
- Participate in code reviews, technical discussions, and implementation of engineering best practices.n
- Work with DevOps teams on CI/CD and deployment automation for data engineering solutions.n
- Troubleshoot and resolve data pipeline and production issues.n

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nMust-Have Skills
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- 6–12 years of experience in Data Engineering / Big Data Engineering.n
- Robust hands-on experience with Azure Databricks and PySpark.n
- Strong experience with Hadoop and its ecosystem.n
- Hands-on experience with Talend for ETL/data integra

📌 Lead Data Engineer (Bengaluru)
🏢 Apexon
📍 Bengaluru