4–6 yrsMumbaiOn-siteDirect career pageEst. 12–20 LPA
Posted 7h ago
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Job description
Structured overview of role & requirements
About This Role
- Design and build scalable, secure, and cost-effective cloud-based data solutions using modern data engineering practices.
- Develop, maintain, and optimize ETL data pipelines for loading data into data warehouses or lakes, ensuring data quality and validation.
- Collaborate closely with analytics leaders, data teams, and stakeholders to deliver actionable business data insights and maintain alignment with analytics agendas.
Minimum Requirements
- 4 to 6 years of experience in data engineering with expertise in the required technology stack.
- Proficiency in Python, PySpark, SQL, and ETL tools such as Databricks, including Medallion Architecture implementations.
- Experience with AWS cloud services (S3, Lambda, EC2, Glue, Redshift) and knowledge of data warehousing concepts including dimensional modeling, SCD types, star schema.
- Work Experience Required: 4 to 6 years; Notice Period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in handling end-to-end cloud-based data engineering projects with a focus on scalable and secure solutions.
- Familiar with integrating multiple data technologies and tools (Databricks, Airflow, AWS services) in a collaborative team environment delivering business analytics.
- Capable of working methodically to meet delivery timelines while maintaining data accuracy and working closely with business analytics and product management teams.