We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the CORPORATE SECTOR, ENTERPRISE TECHNOLOGY, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Develops secure high-quality production code, and reviews and debugs code written by others Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years of applied experience Experience in design and maintain a scalable and efficient data architecture to support financial reporting processes. Experience integrating different data sources by utilizing data modeling tools and software (e.g. SQL, Python, SparkSQL, PySpark) and data visualization tools(e.g. Tableau, ThoughtSpot) Proficient in SDLC CI/CD Execution (GitHub, Jenkins, SNOR, Spinnaker, AIM etc.) Experience across the data lifecycle, Advanced at SQL (e.g., joins and aggregations) Programming languages like Python, Scala, R and/or Java Experience at Git, Scripting, Cloudformation / Terraform Working experience on NoSQL and/or RDBMS databases, ACID, Data Modelling, OLTP, OLAP, Normalization, Denormalization Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns to perform analysis Considerable experience on Distributed Systems like Hadoop, Spark, MapReduce, Kafka Preferred qualifications, capabilities, and skills Sizable experience with AirFlow, Luigi, NiFi, Databricks, Snowflake is a plus Experience customizing changes in a tool to generate data product Provide mentorship, training, and guidance to team members.  Work closely with analytics teams to leverage data for financial analysis and forecasting