Apexon
Website:
apexon.com
Job details:
Job description
Requirement details:
Role: Azure Data Engineer
Location: Bengaluru / 5 days WFO
Interview Process
- Round 1: Face-to-Face Interview
- Round 2: Virtual Techno Manager
Job Summary
We are looking for a Data Engineer with 6to 8 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 to 8 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.
Good to Have
- Experience with Azure Data Lake Storage (ADLS).
- Experience with streaming technologies.
- Knowledge of data governance and security.
- Exposure to data engineering solutions supporting AI/ML workloads.
- Experience with Agile development methodologies.
Click on Apply to know more.
