3+ yrsBengaluruOn-siteDirect career pageEst. 12–20 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, implement, and maintain scalable, fault-tolerant ETL/ELT data pipelines on AWS using services like Redshift, RDS, Glue, and EMR.
- Optimize data workflows with Python, PySpark, and SQL to support business and advanced analytics needs.
- Collaborate with data scientists, analysts, and stakeholders to translate data requirements into technical solutions ensuring data governance, quality, and security.
Minimum Requirements
- Minimum 3 years of experience in developing and managing large-scale data infrastructure and AI applications.
- Proficiency in AWS data services (Redshift, RDS, Glue, EMR) and big data technologies such as Apache Spark or Hadoop.
- Strong skills in Python, PySpark, SQL, data modelling, and database design (SQL and NoSQL).
- Bachelor's degree in Computer Science, Software Engineering, Data Science or related field.
Ideal Candidate Profile
- Experienced with cloud-based data engineering on AWS with a focus on scalability, fault tolerance, and automation.
- Ability to work cross-functionally with data scientists and analysts to deliver business-driven data infrastructure solutions.
- Experienced in promoting and adopting emerging big data technologies, cloud engineering standards, and mentoring junior engineers.