Lead Software Engineer - Java/Python, Data Engineering

JPMorganChase; Hyderabad; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

JPMorgan Chase in Hyderabad is seeking a Lead Software Engineer to advance data-driven risk assessment platforms within the Corporate Sector Data Engineering team. You will deliver secure and scalable solutions for KYC and risk data platforms, setting engineering standards and architecture across multiple teams.

You will mentor engineers, collaborate with senior leaders, and apply cloud, AI/ML, and data engineering practices to build trusted platforms powering the firm's risk management

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale.
• Expert in one or more programming languages, particularly Python and/or Java.
• Advanced knowledge of software application development and technical processes, with considerable depth in one or more disciplines (e.g., cloud, AI/ML, data engineering).
• Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal).
• Advanced 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.

Responsibilities

• Develop secure, high-quality production code for data-intensive applications and platforms, and mentor other engineers.
• Create durable, reusable software frameworks and patterns leveraged across teams and functions.
• Drive adoption of advanced technical methods and practices aligned with industry standards and product development methodologies.
• Advise cross-functional teams on technological matters within your domain of expertise.
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including AI-assisted development and automation capabilities, to improve automation at scale.

Skills

Python

Java

Cloud computing

Data engineering

System design

Communication with leadership

Tools

Kafka

Redis

MemCached

Dynatrace

Splunk

Grafana

Airflow

Temporal

AWS

Azure

GCP

Databricks

Snowflake

Spark/PySpark

Iceberg

Job description

Job Description

Join a team where your engineering expertise drives impactful solutions for a global financial leader. Advance your career while shaping the future of data-driven risk assessment.

Job Summary

As a Lead Software Engineer at JPMorgan Chase within the Corporate Sector Data Engineering team, you deliver secure and scalable solutions that support the firm's Global Know Your Customer (KYC) and Risk Assessment Data Platform. You collaborate with colleagues to drive best-in-class outcomes and set engineering standards. Your leadership helps define architecture and practices across multiple teams. Together, we create trusted platforms that power the firm's critical risk management initiatives.

Job Responsibilities

• Develop secure, high-quality production code for data-intensive applications and platforms, and mentor other engineers
• Create durable, reusable software frameworks and patterns leveraged across teams and functions
• Drive adoption of advanced technical methods and practices aligned with industry standards and product development methodologies
• Advise cross-functional teams on technological matters within your domain of expertise
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including AI-assisted development and automation capabilities, to improve automation at scale

Required Qualifications, Capabilities And Skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale
• Expert in one or more programming languages, particularly Python and/or Java
• Advanced knowledge of software application development and technical processes, with considerable depth in one or more disciplines (e.g., cloud, AI/ML, data engineering)
• Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)
• Advanced 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

Preferred Qualifications, Capabilities And Skills

• Experience with modern data platforms such as Databricks or Snowflake
• Deep hands-on experience with Spark/PySpark and other big data processing technologies
• Expertise in open-source table formats and catalog services such as Apache Iceberg
• Experience with LLM orchestration frameworks and model serving infrastructure or managed endpoints (AWS Bedrock, Azure OpenAI)