Data Engineer

Salary: $61,000 - 101,000 per year Requirements:

• Bachelors degree in Computer Science, Information Technology, or a related field
• At least 3 years of data engineering experience, with strong expertise in AWS, data lakes, and Snowflake
• Hands-on experience with modern data lake and data warehousing technologies such as Redshift, BigQuery, or Snowflake, and processing engines such as Spark, Flink, or Trino
• Proficiency in SQL and experience with data pipeline or ETL tools
• Experience applying Agile methodologies, facilitating ceremonies, and prioritizing backlogs for continuous improvement
• Demonstrated experience using enterprise-authorized AI capabilities in the work environment to support data engineering, with careful validation and awareness of data sensitivity
• Ability to review and validate AI-assisted outputs, escalate questions when uncertain, and follow data handling requirements
• Experience designing and building streaming pipelines with Kafka, Pub/Sub, or similar messaging systems
• Experience with large-scale distributed data processing and performance tuning
• Ability to design and implement large-scale data solutions in cloud environments
• Preferred: Experience with data modeling in Erwin
• Preferred: Experience with table formats such as Iceberg or Hudi

• Design, build, maintain, and optimize scalable batch and streaming data pipelines, ensuring performance, fault tolerance, and observability
• Develop and operate workflow orchestration to schedule, monitor, and manage data movement and transformations
• Translate complex business needs into technical solutions that meet data lake and data warehouse standards
• Use enterprise-authorized AI capabilities to support pipeline design and analysis, and documentation, validating results and protecting sensitive data
• Apply reuse-first, AI-assisted practices to improve SDLC quality for data pipelines, including test generation and control validation, while maintaining traceability and meeting resiliency and security expectations
• Establish and maintain data governance processes for modeling, cataloging, ownership, and access control
• Mentor and train team members on data publication best practices, and guide technical direction through standards, reviews, and knowledge sharing
• Keep current with AWS Data Lake, Snowflake Data Warehouse, and related technologies
• Analyze large datasets using advanced quantitative methods to identify business trends
• Manage data sharing, exchange, and ecosystem-specific features

• AI
• AWS
• Redshift
• BigQuery
• Cloud
• Data Warehouse
• ETL
• Flink
• Support
• Kafka
• SQL
• Security
• Snowflake
• Spark

More:

We are partnering with hackajob to connect exceptional professionals with J.P. Morgan for a Data Engineering III role on our Consumer and Community Banking team. In this position, you will help deliver scalable, secure, and efficient data solutions that support business objectives and regulatory needs, contributing your expertise to a collaborative, high-performing team. We are a leading financial services firm serving households, small businesses, nonprofits, and cities, with a mission to build lasting customer relationships and put customers first. Our Consumer & Community Banking division provides services including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans, and payment processing. We offer a competitive total rewards package, with salary based on role, experience, skills, and location; eligible roles may also include incentive compensation. Benefits, subject to eligibility, include health care coverage, wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching. We value diversity and inclusion, are an equal opportunity employer, and provide reasonable accommodations for applicants and employees.

last updated 40 week of 2026