AWS Engineer
Fractal (company site, opens in a new tab)3–4 yrsBengaluruOn-siteDirect career pageEst. 12–20 LPA
Posted 13h ago
Reach people at Fractal
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 Fractal 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, test, and deploy scalable ETL/ELT data pipelines using AWS Databricks, PySpark, and SQL.
- Build and maintain data solutions handling structured and unstructured data across AWS services including S3, RDS, and Delta Lake for batch and streaming workloads.
- Collaborate with cross-functional teams to ensure data quality, performance optimization, pipeline orchestration, and support CI/CD deployment processes.
Minimum Requirements
- 3–4 years of experience in Data Engineering or similar role.
- Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
- Strong hands-on experience with AWS Databricks, PySpark, SQL, and Delta Lake.
- Familiarity with AWS data services (S3, RDS, Glue, Lambda, Redshift) and workflow orchestration tools (e.g., AWS Glue Workflows, Apache Airflow).
Ideal Candidate Profile
- Experienced in building and optimizing enterprise-scale cloud data pipelines primarily on AWS Databricks ecosystem.
- Skilled in both batch and streaming data architectures with strong focus on data quality, governance, and operational monitoring.
- Comfortable collaborating with data scientists, analysts, and architects in an agile, fast-paced environment with ownership of delivery and troubleshooting.