Data Engineer -Databricks
ShyftLabs (company site, opens in a new tab)4+ yrsCoimbatoreHybridDirect career pageEst. 12–20 LPA
Posted on 22 Sept
Reach people at ShyftLabs
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at ShyftLabs you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain scalable ETL/ELT pipelines on Databricks Lakehouse Platform using PySpark, SQL, and Python.
- Integrate data from multiple sources including databases, Amazon S3, and REST APIs, applying business logic and dimensional modeling (Medallion Architecture).
- Schedule, monitor, optimize Databricks Jobs and Workflows ensuring data quality, error handling, and Spark performance tuning.
Minimum Requirements
- Strong expertise in Python, PySpark, advanced SQL, and hands-on experience with Databricks Lakehouse Platform.
- Experience with Unity Catalog, Delta Lake, Databricks Workflows/Jobs, and Medallion Architecture for data pipelines.
- Work Experience Required: Minimum 4 years in Data Engineering with at least 2 years using Databricks.
- Experience with REST API integrations and knowledge of ETL/ELT development, batch processing, incremental loading, and data modeling (Star Schema, SCD).
Ideal Candidate Profile
- Proven track record of delivering production-ready data pipelines in environments relying on Databricks and Spark performance optimization.
- Experienced in handling large-scale structured and semi-structured data in cloud environments (AWS preferred).
- Familiar with version control (Git), CI/CD best practices, and preferably with Databricks certification or experience using related tools like Auto Loader, Kafka, or Airflow.