Sr Lead Software Engineer - Data Engineering
JPMorgan Chase14 hours ago
Responsibilities
- Design and deliver reusable frameworks and platforms for high-throughput real-time applications and large-scale batch processing with Spark.
- Write production code daily and lead design quality, testing, operational readiness, and technical direction.
- Lead a Scrum team by decomposing complex problems, unblocking engineers, and setting technical standards without a reporting line.
- Mentor engineers, improve code-review standards, and build the team’s technical capability.
- Provide guidance on data governance, quality, profiling, lineage, acquisition, maintenance, validation, and utilization.
- Design trusted data collection, storage, access, and analytics solutions across AWS, Databricks, and Snowflake.
- Build streaming and low-latency serving components using Kafka, Cassandra, and AWS services.
- Partner with product, architecture, modeling, and model-deployment teams to deliver data engineering solutions.
- Use authorized generative and agentic AI capabilities to accelerate engineering work while validating outputs and protecting sensitive data.
- Present technical designs, platform metrics, and data insights to engineering and business stakeholders.
Requirements
- Formal training or certification in software engineering concepts and 5+ years of applied experience.
- Strong hands-on programming expertise in Java, Python, and Scala.
- Experience building reusable frameworks and platforms adopted by other teams.
- Experience delivering high-throughput real-time systems and high-volume Spark processing over very large datasets, including performance tuning at scale.
- Deep hands-on experience with AWS and Databricks, including Unity Catalog, Delta Lake, Lakeflow, Delta Live Tables, Catalog Sharing, fine-grained access control, and SQL Warehouses.
- Production experience with Snowflake in a data platform environment.
- Working experience with Kafka, Cassandra, and AWS streaming and NoSQL offerings.
- Strong understanding of relational and NoSQL databases and their data-modeling trade-offs.
- Experience using authorized generative AI capabilities to accelerate engineering delivery, with strong validation and data-sensitivity awareness.
- Experience working on AI/ML systems and understanding of decision trees, ensemble methods, neural networks, and transformer models.
- Preferred qualifications include mentoring engineers, AWS, Databricks, or Snowflake certifications, data governance experience in regulated environments, Unity Catalog Feature Store experience, agentic AI tooling adoption, and cloud migration or platform modernization experience.
Benefits
- Competitive total rewards package with base salary determined by role, experience, skill set, and location, plus potential incentive compensation for eligible roles.
- Comprehensive health care coverage, on-site health and wellness centers, retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching.
- Equal opportunity employer with reasonable accommodation support for religious practices, mental health needs, and physical disabilities.
Tech Stack
Categories
BackendData 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.