3–7 yrsMumbaiOn-siteDirect career pageEst. 12–28 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Design and build scalable, secure cloud-based data solutions and maintain data pipelines using AWS and Databricks technologies.
- Implement and optimize ETL processes and data storage for efficient data retrieval and quality assurance in data warehouses or lakes.
- Collaborate closely with data teams and stakeholders to execute business analytics agenda and deliver insights for long-term business performance.
Minimum Requirements
- 3 to 7 years of experience in data engineering with expertise in Python, PySpark, SQL, Databricks, and AWS services (S3, Lambda, EC2, Glue, Redshift).
- Proficient in data modeling including dimensional modeling and ETL concepts (SCD Types, star schema), with knowledge of Medallion Architecture.
- Experience with scheduling tools such as Lakeflow Jobs or Airflow is required; GenAI exposure is a plus.
- Notice period: 0-3 months; No relocation support; Work Experience Required: 3 to 7 years.
Ideal Candidate Profile
- Experienced in cloud-based, scalable data platform design with strong hands-on skills in modern data engineering stacks (Databricks, AWS).
- Able to produce and optimize robust data pipelines ensuring data quality, accuracy, and performance at scale.
- Comfortable working in cross-functional teams and collaborating with analytics leaders and product managers to translate business needs into technical solutions.