Lead Software Engineer
JPMorgan Chase6 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Lead evaluations of external vendors, startups, and internal teams by assessing architecture, technical credentials, and applicability to existing systems.
- Drive adoption of enterprise-authorized AI-assisted engineering practices and establish standards for validating their correctness, performance, and security.
- Lead architecture and engineering for large-scale data processing and platform solutions using Python and Java.
- Design and implement ETL/ELT pipelines covering ingestion, transformation, validation, reconciliation, and publishing across curated data layers.
- Build and operationalize Medallion architecture patterns for data quality, lineage, governance, and reuse.
- Develop and optimize data lake partitioning strategies.
- Apply software engineering best practices including code quality, testing, CI/CD, observability, security-by-design, and operational readiness.
- Optimize Apache Spark jobs, storage layouts, and Snowflake workloads.
- Partner with product owners, architects, data governance teams, and downstream consumers to deliver resilient technical solutions.
Requirements
- Formal training or certification in software engineering concepts and 5+ years of applied experience.
- Experience leading the effective use of approved AI-assisted software development tools and validating their outputs for correctness, performance, and security.
- Understanding of responsible AI use, data sensitivity, secure input and output handling, resiliency, and security expectations, including coaching engineers on compliant adoption.
- Strong hands-on development skills in Python and/or Java.
- Strong experience with Apache Spark and distributed data processing.
- Expertise building ETL/ELT pipelines and data integration frameworks.
- Understanding of data storage, serialization, and table/file formats including Parquet and Avro.
- Deep knowledge of distributed compute, fault tolerance, partitioning, data quality, and metadata management.
- Strong experience with Medallion architecture and data lake design principles.
- Working knowledge of Snowflake loading, unloading, and performance considerations.
- Ability to lead technical decisions, align teams, and communicate with technical and non-technical stakeholders.
- Preferred qualifications include experience with data orchestration, pipeline automation, data governance, production operations, streaming, event-driven processing, incremental processing, reusable data products, regulated environments, lakehouse patterns, data platform modernization, and FinOps-style cost controls.
Tech Stack
Categories
Data Engineering
About JPMorgan Chase
JPMorgan Chase provides consumer and commercial banking, payments, credit card, wealth management, and corporate and investment banking services to individuals, businesses, institutions, and governments. The public company (NYSE: JPM) earns revenue from interest, fees, trading, and asset management across operations in more than 100 markets. Headquartered in New York City with roots dating to 1799, it serves retail customers and prominent corporate and government clients through brands including Chase and J.P. Morgan.