Bulge Bracket Investment Banks

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**Software Engineer III - Python, Spark/PySpark, Databricks, SQL** in Bengaluru, India. Develops ELT data pipelines using Python, Spark/PySpark, and Databricks, architecting scalable systems for enterprise analytics. Employs SQL extensively, working with both relational and NoSQL data stores. Applies best practices, optimizes performance, and maintains data security. Partners with stakeholders to deliver production-ready solutions and collaborates in agile teams. Proficient in SDLC practices, including CI/CD, testing, and deployment. Prioritizes code quality using AI-assisted tools. Requires 3+ years of software engineering experience with Databricks, Spark, Python, and SQL. Experience with cloud platforms (AWS) and data processing is a plus.

Compensation: Not specified
City: Bengaluru
Country: India

Full Job Description

Location: Bengaluru, Karnataka, India

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III - Python, Spark/PySpark, Databricks, SQL at JPMorgan Chase within the Commercial & Investment Bank, you'll serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives.

Job responsibilities

Develop workflows and ELT data pipelines using Python, Spark/PySpark, and Databricks

Build, test, and maintain scalable data pipelines and data architectures that support enterprise analytics use cases

Apply data engineering best practices for performance optimization, reliability, and maintainability and Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Support implementation of data security, governance, and entitlements frameworks to protect enterprise data

Use SQL extensively and work with both relational and NoSQL data stores

Partner with stakeholders to understand data requirements and translate them into production-ready solutions

Apply SDLC practices including CI/CD, testing, and operational monitoring to ensure pipeline stability

Contribute to reusable frameworks and standards to accelerate onboarding and pipeline delivery

Identify data issues, anomalies, and optimization opportunities to improve data quality and performance

Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.

Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 3+ years applied experience
Hands-on experience with Databricks, Spark/PySpark, Python, and SQL
Experience developing and maintaining data pipelines and data processing systems
Understanding of the data lifecycle, including ingestion, transformation, storage, and consumption
Knowledge of cloud platforms (AWS) and distributed data processing
Experience with SDLC practices including CI/CD, testing, and deployment
Strong problem-solving skills and ability to troubleshoot data and pipeline issues
Ability to collaborate effectively within agile teams and across stakeholders
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred qualifications, capabilities, and skills

Experience with Databricks lake house, Delta Lake, and medallion architecture

Exposure to data quality, observability, and metadata management tools

Experience supporting analytics, reporting, or AI/ML workloads

Familiarity with modern front-end technologies

Exposure to cloud technologies

Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team

Full Job Description