Senior Data Engineer
Bangalore, India (Hybrid)

About Symphony Technology Group (STG)
STG is a Silicon Valley (California) based private equity firm with a long and successful track record of transforming high-potential software and software-enabled services companies, as well as insights-oriented companies, into definitive market leaders. The firm brings expertise, flexibility and resources to build strategic value and unlock the potential of innovative companies. Partnering to build customer-centric, market-winning portfolio companies, STG creates sustainable foundations for growth that bring value to all existing and future stakeholders. The firm is dedicated to transforming and building outstanding technology companies in partnership with world-class management teams. Founded in 2002, STGs portfolio has consisted of more than 50 global companies, and the firm currently manages over $12 billion in assets under management (as of March 2025). Learn more: https://stg.com

About STG Labs
STG Labs is the incubation center for many of STG’s portfolio companies, building their engineering, professional services and support delivery teams in India. STG Labs offers an entrepreneurial start-up environment for software and AI engineers, data scientists and analysts, project and product managers, and provides a unique opportunity to work directly for a software or technology company. STG has supported its portfolio companies in building teams in India since 2003, and STG Labs is headquartered in a 19,000 square foot office in Bangalore, with teams across multiple locations in India. Learn more: https://stglabs.com

About Yodlee
Yodlee is an open finance, data aggregation and analytics company with a 25-year history in financial data. It provides secure data access and analytics that help financial institutions and their clients make better use of financial data. Yodlee was acquired from Envestnet by STG, with the sale announced in June 2025 and completed in September 2025. Under STG, Yodlee is focused on operating with greater agility, speeding up time to market and expanding its open finance offerings. The Data Management team works with STG Labs in Bangalore to build the cloud data platform behind these products. Learn more: https://www.yodlee.com

Domain: Open Finance & Financial Data Aggregation

Role Overview
As a Senior Data Engineer in Analytics Engineering – Data Management, you will design, build, deploy and optimise data pipelines and platform components on AWS. You will work closely with Analytics Engineering, Data Science, DevOps, QA and Product teams to deliver scalable,



secure and reliable pipelines and curated data assets. You will play a key role in building and evolving the AWS-based Data Lake through robust ingestion, transformation and processing frameworks.

Key Responsibilities

Product & Technology Delivery

- Deliver Data Lake capabilities: Partner with Product, Analytics, Insights and Technology teams to align short-term delivery with long-term platform goals.
- Build pipeline frameworks: Enhance ingestion, curation, transformation and access layers for downstream analytics and model delivery.
- Evolve engineering standards: Contribute reusable components and development best practices across the Data Management team.

Building Scalable Data & Analytics Solutions

- Develop AWS data pipelines: Design and maintain scalable pipelines for ingestion, storage, transformation and delivery of structured and semi-structured data.
- Implement batch and real-time processing: Support analytics, reporting and enrichment or model-driven use cases.
- Build curated data layers: Create reusable transformation logic that balances scalability, performance, reliability, maintainability and cost.
- Support Data Lake standards: Partitioning, schema evolution, lineage, observability and data quality.

Technical Execution & Mentorship

- Lead complex components: Own development of complex data engineering components and mentor junior engineers on implementation best practices.
- Build cloud-native frameworks: Use Python, Spark, SQL and AWS-native services for data processing.
- Translate requirements into solutions: Turn functional and technical needs into production-ready engineering, and contribute to design reviews against architectural standards.

Quality, Governance & Engineering Excellence

- Ensure code quality: Perform code reviews, unit and integration testing, and performance tuning.
- Operate critical pipelines: Implement monitoring, alerting, logging and recovery mechanisms.
- Meet enterprise standards: Keep pipelines and datasets compliant on data governance, security and operational readiness.
- Improve outcomes: Drive measurable gains in pipeline reliability, performance, supportability and cloud cost optimisation.





Agile Collaboration & Innovation

- Collaborate across Agile teams: Work with Data Management, Models Delivery, Insights Ops and Insights, plus product managers, architects, analysts and operations, to refine requirements and ship production-ready solutions.
- Stay current and evaluate tools: Track cloud data platform practices, assess tools that improve productivity and efficiency, and mentor junior engineers.

Required Qualifications & Skills

Must-Have (Hands-on)

- 7+ years in data engineering, analytics engineering, platform engineering or software development, with strong hands-on Python, SQL, Scala or Java.
- 5+ years with public cloud platforms, preferably AWS.
- 5+ years with distributed data and compute technologies such as Spark, EMR, Hadoop, Hive, Kafka and relational databases.
- Robust hands-on experience with AWS data services including S3, Glue, Athena and EMR, and working knowledge of Lake Formation, IAM and KMS.
- Strong experience with Spark/PySpark, SQL optimisation, data modelling and large-scale transformation workflows.
- 3+ years building scalable distributed data pipelines and production-grade applications, including streaming and real-time processing.
- 3+ years with data warehousing technologies such as Redshift, Snowflake or equivalent cloud analytics platforms.
- 3+ years with NoSQL platforms such as MongoDB or Cassandra.
- 3+ years with UNIX/Linux, shell scripting and production troubleshooting.
- 2+ years mentoring engineers or leading major technical workstreams.
- Strong understanding of data governance, metadata, lineage, quality controls, compliance and operational support.
- Experience with CI/CD, version control, Infrastructure as Code and engineering automation.
- Strong communication, documentation and stakeholder collaboration skills across engineering, analytics and operations teams.

Secondary Skills

- Experience working in AWS Data Lake environments.
- Experience with modern table formats such as Apache Iceberg or Delta Lake.
- Experience in financial services, banking, card or transaction data domains.
- Experience supporting analytics, insights and model delivery use cases on a shared Data Lake platform.
- Experience with data quality frameworks, metadata-driven pipelines and reusable ingestion frameworks.

Education / Qualifications

- Bachelor’s degree in Computer Science, Engineering, Information Systems or a related field, with relevant experience; Master’s degree is a plus.

Work Mode: Hybrid. This role adheres to the organization’s hybrid work policy.

📌 Senior Data Engineer (Bengaluru)
🏢 STG Labs
📍 Bengaluru