Role: Senior Software Engineer – Java & PySpark
Function: Software Engineering / Data Engineering
Location: Bangalore
Type: Full-time
Industry: Technology, Financial Services, Retail, Healthcare, Manufacturing, Telecommunications
About Company
A technology consulting and digital engineering firm partnering with Fortune companies and high-growth businesses. The company delivers across Product Engineering, Cloud, Data & Analytics, AI, Generative AI, DevOps, Cybersecurity, and Enterprise Applications.
It serves industries including Financial Services, Retail, Healthcare, Manufacturing, and Telecommunications. Backed by leading investors and guided by experienced tech leaders from top global firms.
The company is driven by engineering excellence, agility, and a product-first mindset.
Position Overview
This role carries equal ownership across backend microservices engineering and large-scale data pipeline development, delivered directly for enterprise clients across regulated industries. The engineer will be embedded in client delivery engagements, translating complex business and data requirements into production-grade Java services and PySpark pipelines. Impact is measured by the reliability, scalability, and performance of systems that underpin critical client operations.
Role & Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines using PySpark and Apache Spark (Core, SQL, DataFrames, Streaming) for enterprise client engagements
- Build and own backend microservices using Java 8+ and Spring Boot, exposing well-structured REST APIs as part of client delivery workstreams
- Integrate data from heterogeneous sources — relational databases, NoSQL stores, APIs, and streaming platforms — ensuring consistency and reliability across client environments
- Perform Spark job tuning and Java application optimization to meet client-defined latency and throughput SLAs at large dataset scale
- Enforce data quality, security, and governance standards across pipeline and service layers in line with client compliance requirements
- Troubleshoot and resolve production incidents across data and backend layers with minimal client downtime
- Collaborate directly with client stakeholders, data scientists, and analysts to translate analytical and operational requirements into robust, reusable engineering solutions
Must Have Criteria
- 6+ years of hands-on experience with Java 8+, including strong OOP design and REST API development
- 6+ years building data pipelines with PySpark / Apache Spark (Core, SQL, DataFrames, Streaming)
- Proficiency in Spring / Spring Boot and microservices architecture
- Experience with relational databases (PostgreSQL, MySQL, or Oracle) and writing complex SQL queries
- Experience with at least one NoSQL database — MongoDB, Cassandra, or DynamoDB
- Hands-on experience with Hibernate / JPA for ORM in Java applications
- Demonstrated ability to process and optimize large-scale datasets in distributed computing environments
Nice to Have
- Prior experience in a client-facing consulting or digital engineering delivery environment
- Exposure to real-time or near-real-time streaming pipelines using Spark Structured Streaming
- Familiarity with cloud platforms — AWS, Azure, or GCP — for pipeline and service deployment
- Domain experience in regulated industries such as Financial Services, Healthcare, or Retail
What We Offer
- Exposure to large-scale, high-complexity client engagements across Fortune-class enterprises in multiple industries
- Mentorship from industry experts and leadership with pedigree from top global technology firms
