Software Engineer III - Python, PySpark, Databricks, Big Data

JPMorganChase; Hyderabad; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

JPMorgan Chase is seeking a Software Engineer III to contribute to a trusted Global KYC and Risk Assessment Data Platform. You will work within an agile data engineering team, delivering secure, scalable software that enables smarter decisions across firm portfolios.

You will apply expertise in distributed data processing, cloud-native architectures, and AI-assisted development while collaborating with stakeholders and mentors to uphold engineering excellence.

Qualifications

• Hands-on experience delivering system design, application development, testing, and operational stability at enterprise scale.
• Proficiency in Python and/or Java with strong software engineering practices.
• Experience with large-scale data processing, microservices, API design, and data governance.

Responsibilities

• Develop secure, high-quality production code for data-intensive applications and platforms.
• Create durable, reusable software frameworks and patterns leveraged across teams and functions.
• Advise cross-functional teams on technological matters within your domain of expertise.
• Apply knowledge of SDLC tools and AI-assisted development to improve automation and code quality.

Skills

Python

Java

Cloud platforms

Data engineering

Kafka

Redis

Observability

Airflow

Temporal

SQL/NoSQL

Tools

Databricks

Snowflake

Spark/PySpark

Apache Iceberg

Airflow

Job description

Job Description

Join us to engineer a trusted data platform that helps protect customers and the firm while enabling smarter, faster decisions, you'll grow your skills alongside experienced engineers, collaborate across teams, and ship high-impact software that scales.

Job Summary

As a Software Engineer III at JPMorgan Chase within the Corporate Sector, you serve as a seasoned member of an agile data engineering team, building and delivering a trusted Global Know Your Customer (KYC) and Risk Assessment Data Platform in a secure, stable, and scalable way, you leverage your technical capabilities and collaborate with colleagues across the organization to promote best-in-class outcomes across technologies that support one or more firm portfolios, you help uphold strong engineering practices and deliver high-impact software that scales across multiple teams.

Job Responsibilities

• Develop secure, high-quality production code for data-intensive applications and platforms
• Create durable, reusable software frameworks and patterns leveraged across teams and functions
• Advise cross-functional teams on technological matters within your domain of expertise
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve value realized by automation at scale

Required Qualifications, Capabilities, And Skills

• Hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale
• Expertise in one or more programming languages, particularly Python and/or Java
• Deep knowledge of software application development and technical processes, with considerable depth in one or more disciplines (for example, cloud, artificial intelligence/machine learning, or data engineering)
• Experience with large-scale data processing, microservices, API design, Kafka, Redis, Memcached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)
• Working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance
• Practical cloud-native experience (AWS, Azure, or GCP)
• Ability to present and effectively communicate with senior leaders and executives
• 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.

Preferred Qualifications, Capabilities, And Skills

• Experience with modern data platforms (e.g., Databricks, Snowflake) and building solutions on cloud-native data ecosystems.
• Strong hands-on big data engineering skills, including Spark/PySpark and related distributed processing technologies.
• Deep expertise in open table formats and metadata/catalog services, such as Apache Iceberg, for scalable, governed data management.
• Experience with large language model (LLM) orchestration frameworks and model serving/managed endpoint infrastructure (e.g., AWS Bedrock, Azure OpenAI).
• Proficient in enterprise-authorized AI-assisted development tools and responsible AI engineering practices—able to validate/refine AI outputs for correctness, performance, and security while guiding peers on safe, compliant usage.

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