About the role
Corporate Technology - Lead Data Engineer
Chicago, IL, United States
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Job Information
Job Identification
210785892
Job Category
Data Engineering
Business Unit
Corporate Sector
Posting Date
09/23/2026, 12:37 PM
Locations
10 S Dearborn St, Chicago, IL, 60603, US
Job Schedule
Full time
Job Shift
Day
Base Pay/Salary
Chicago,IL $133,000.00-$175,000.00
Job Description
Join a team that designs and develops scalable and secure distributed architectures and solutions, focusing on data ingestion and processing utilizing appropriate cloud native technologies and services.
As a Lead Data Engineer, within our Corporate Technology Team, you will design, implement, and maintain data pipelines that efficiently collect, process, and store large volumes of data from various sources, ensuring data timeliness, quality, and completeness, and ensure that data solutions comply with relevant data residency and privacy regulations, and implement best practices for securing data at rest and in transit in compliance with financial regulations and firm wide policies.
Job Qualifications:
Design and develop scalable and secure distributed architectures and solutions, focusing on data ingestion and processing - utilizing appropriate cloud native technologies and services.
Data pipeline development: Design, implement, and maintain data pipelines that efficiently collect, process, and store large volumes of data from various sources, ensuring data timeliness, quality, and completeness.
Security and compliance: Ensure that data solutions comply with relevant data residency and privacy regulations, and implement best practices for securing data at rest and in transit in compliance with financial regulations and firm wide policies.
Engages technical teams and business stakeholders to discuss and propose technical approaches to meet current and future needs
Defines the technical target state of their product and drives achievement of the strategy
Evaluates recommendations and provides feedback on new technologies
Executes creative software solutions, design, and development
Required Qualifications, capabilities, and skills:
Programming: Comfortable with Java/Python including sound testing and code review practices.
SQL expertise: Joins, aggregations, subqueries, window functions
Data pipelines: Design, build, and optimize production ETL/ELT pipelines (batch + streaming) using a popular framework (Spark, Flink, Dataflow, etc).
Streaming: Hands-on with Kafka (topics, keys, partitions, consumer groups) at-least-once semantics, and schema registry basics.
Warehousing/Lakehouse: Data modelling, partitioning, clustering. Hands-on with one of Snowflake, Databricks, etc, and cloud storage or HDFS.
Cloud: Production experience with at least one major cloud provider (GCP/AWS) using native data services . FinOps-aware with cost-effective design.
Reliability: Data quality checks, backfills, incorporating SLIs with observability and reporting and lakehouse platforms and table formats (Delta/Iceberg/Avro/Parquet) and time-travel.
Preferred qualifications, capabilities, and skills:
Experience with Kafka, Flink, or other streaming technologies.
Familiarity with AI/ML technologies including LLMs, prompt engineering, vector search, and responsible AI practices and experience using AI-assisted software development tools such as GitHub Copilot, Claude, or similar technologies.
Financial services industry experience and understanding of large-scale enterprise data environments.
Experience mentoring engineers and leading technical delivery initiatives.
Minimum requirements
- Proficient in Java/Python programming, SQL, and building production ETL/ELT pipelines using frameworks like Spark or Flink.
- Hands-on experience with Kafka streaming, data warehousing/lakehouse technologies (Snowflake, Databricks), and cloud platforms (GCP/AWS).
- Knowledge of data security, compliance, data quality, and reliability practices in financial or enterprise environments.
This listing was parsed by AI and may not be complete. Check the official posting on JPMorganChase's site for the most accurate information.