Databricks Data Engineer
Infosys
Bengaluru East, Karnataka, India4m agovia LinkedIn
This job at a glance
- Who can apply
- Freshers
- Must know
- SparkETLREST APIsTroubleshootingSQLAWS
- Work
- On-site in Bengaluru East
- Pay
- Not stated by the employer.
- Skill demand
- REST APIs9%Troubleshooting3%of 32 similar fresher jobs posted in India this week
- Listed
- 2 Nov 2026 · still open
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About the Role
As a Databricks Data Engineer at Infosys, you will work on enterprise-scale data modernization programs involving Lakehouse implementations, cloud migrations, real-time analytics, and AI-ready data ecosystems.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark.
- Build and optimize ETL/ELT workflows for processing large-scale structured and unstructured datasets.
- Develop data ingestion frameworks to integrate data from multiple sources, including databases, APIs, applications, and cloud storage.
- Implement and manage Lakehouse architecture using Databricks and Delta Lake.
- Optimize Spark jobs and Databricks workloads for performance, scalability, and cost efficiency.
- Collaborate with analytics, BI, and business teams to understand data requirements and deliver reusable data assets.
- Implement data quality frameworks, monitoring solutions, and governance controls across data pipelines.
- Troubleshoot production issues and provide timely resolution to ensure business continuity.
- Participate in architecture reviews, code reviews, and technical discussions to promote best practices.
- Create and maintain technical documentation, reusable components, and deployment standards.
Requirements & Tech Stack
- Strong hands-on experience with Databricks.
- Proficiency in PySpark or Spark SQL for distributed data processing.
- Strong SQL skills with experience in query optimization and performance tuning.
- Experience in designing and developing ETL/ELT pipelines.
- Hands-on experience with Delta Lake, DataFrames, and Spark architecture.
- Knowledge of data warehousing concepts, dimensional modeling, and data lake architectures.
- Experience working with cloud platforms such as Azure, AWS, or GCP.
- Familiarity with Git-based source code management and DevOps practices.
- Strong analytical, debugging, and problem-solving skills.