Lead Software Engineer Data and Payments Data Platform

Testing Site - JPMC; Austin (TX); In loco; USD 180.000 - 240.000; Tempo pieno

Descrizione del lavoro

JPMorgan Chase in Austin, TX seeks a Lead Software Engineer - Data and Payments Data Platform to drive scalable, secure data solutions across the firm. You will lead design and development of data pipelines, governance layers, and production-grade components with cross-functional teams.

You will mentor engineers, advance CI/CD practices, and evaluate new technologies like Spark, Flink, Airflow, and Databricks to deliver reliable analytics and payment data platforms for business stakeholders.

Competenze

• 5+ years of applied software engineering experience.
• 3+ years in data engineering or data platform development.
• Experience with distributed data processing frameworks like Spark and Flink.
• Proficiency in building scalable data pipelines and ETL/ELT workflows.
• Experience with Databricks and Airflow.
• Cloud data services experience (AWS).
• Strong SDLC and agile practices.

Mansioni

• Executes creative software solutions, design, development, and technical troubleshooting.
• Designs, builds, and maintains scalable data pipelines and ETL/ELT workflows for batch and real-time processing using Spark, Airflow, Kafka, and Flink.
• Develops data platform components including data cataloging, data quality frameworks, and semantic/metrics layers with governance, lineage, and compliance standards.
• Implements data modeling strategies (fact and dimensional) to support analytics, reporting, and downstream consumption.
• Partners with analytics teams, product managers, and business stakeholders to translate data requirements into production-grade solutions.
• Develops secure high-quality production code, and reviews and debugs code written by others.
• Identifies opportunities to automate remediation of recurring issues to improve operational stability.
• Leads evaluation sessions with vendors and teams to drive architecture assessments.
• Leads communities of practice across Software Engineering for new technologies.
• Adds to team culture of diversity, opportunity, inclusion, and respect.

Conoscenze

Python

Java

SQL

CI/CD

Agile methodologies

Formazione

Formal software engineering training

Strumenti

Apache Spark

Apache Flink

Apache Airflow

Databricks

AWS S3

Glue

Redshift

Athena

EMR

Descrizione del lavoro

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 - Data and Payments Data Platform at JPMorgan Chase within the Commercial and Investment Banking - Data Analytics Payment team, 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
• Designs, builds, and maintains scalable data pipelines and ETL/ELT workflows for batch and real-time processing using Spark, Airflow, Kafka, and Flink
• Develops data platform components including data cataloging, data quality frameworks, and semantic/metrics layers with embedded governance, lineage, and compliance standards
• Implements data modeling strategies (fact and dimensional, wide tables) to support analytics, reporting, and downstream consumption
• Partners with analytics teams, product managers, and business stakeholders to translate data requirements into production-grade solutions
• 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, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• 3+ years of professional experience focused on data engineering or data platform development
• Advanced in one or more programming languages(s); Python, Java and SQL
• Hands-on experience with distributed data processing frameworks such as Apache Spark and Flink
• Solid understanding of data modeling techniques (star schema, snowflake) and query optimization
• Experience designing and operating data pipelines on Databricks using orchestration tools such as Apache Airflow
• Proficiency with cloud data services (AWS S3, Glue, Redshift, Athena, EMR, Lake Formation, or equivalent)
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

Preferred qualifications, capabilities, and skills

• Exposure to LLMs, RAG architectures, vector databases, and embedding-based retrieval systems
• Experience with data mesh or data product architectures
• Proficiency with Infrastructure as Code (Terraform) and containerized deployments (Docker, Kubernetes)
• Experience with data observability, quality, and metadata management tools
• Experience with semantic layers, metrics stores, or BI platforms (Tableau, dbt Metrics)