Data Engineer
MerQube (company site, opens in a new tab)4–7 yrsBengaluruOn-siteDirect career pageEst. 12–22 LPA
Posted on 10 Sept
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
Reach people at MerQube
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 MerQube you could write to:
- Recruiters & HR
- People in this function
- Work addresses
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, build, and maintain scalable AWS-based ETL/ELT data pipelines and lakehouse platforms for transactional and analytical workloads.
- Modernize legacy ETL frameworks to standardized, cloud-native AWS data platforms supporting index construction and analytics.
- Implement data quality, governance, and validation frameworks to ensure data accuracy and support financial index calculations.
Minimum Requirements
- Bachelor’s Degree in Computer Science, Engineering, Mathematics, or equivalent experience.
- 4–7 years of experience as a Data Engineer in fintech, trading, market data, or financial analytics preferred.
- Strong programming skills in Python and solid SQL expertise; experience with AWS services like S3, Glue, Lambda, Athena/Redshift.
- Experience building batch and/or streaming ETL pipelines and working with large, heterogeneous datasets.
Ideal Candidate Profile
- Experienced in fintech or financial data engineering environments with domain knowledge of market data and financial instruments.
- Skilled in modern cloud-native data architectures, particularly AWS, and capable of transforming legacy ETL systems.
- Demonstrated ability to collaborate cross-functionally to translate complex financial logic into scalable data solutions.