Senior Data Engineer, DaS FinTech
Amazon Web Services (AWS) (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 30–50 LPA
Posted on 9 Sept
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Job description
Structured overview of role & requirements
About This Role
- Develop and manage scalable, automated, fault-tolerant data pipelines using Spark, EMR, Python, Redshift, Glue, and S3 to support analytics, reporting, and operations.
- Lead design and code reviews to enforce engineering best practices across data development, documentation, testing, and monitoring.
- Drive data governance, cost optimization, measurement infrastructure for experiments, and provide self-service data access through metadata catalogs and governed query layers.
Minimum Requirements
- 5+ years of data engineering experience.
- Experience with data modeling, data warehousing, and building ETL pipelines using SQL and at least one scripting/programming language (Python, Java, Scala, or NodeJS).
- Work Experience Required: Minimum 5 years in data engineering; Experience mentoring team members on best practices.
- Not explicitly mentioned: formal degree requirements, notice period, or strict onsite/location mandates.
Ideal Candidate Profile
- Experienced in leading and architecting large-scale data solutions, preferably with AWS data services (Redshift, S3, Glue, EMR, Kinesis, Lambda).
- Strong familiarity with big data technologies (e.g., Hadoop, Hive, Spark, EMR) and building data platforms supporting batch and real-time analytics.
- Capable of bridging technical and business requirements, providing technical leadership, mentoring engineers, and driving data governance and cost optimization strategies.