Lead Data Architect, Consumer Card Technology

JPMorgan Chase JPMorgan Chase · Banking · Wilmington, DE +1 · Consumer & Community Banking

Lead Data Architect for Consumer Card Technology at JPMorgan Chase, focusing on designing and implementing high-quality data architecture solutions for software applications and platform products. Responsibilities include driving data architecture decisions, collaborating with teams, designing frameworks, mapping data requirements, performing data completeness checks, evaluating technologies, and serving as a subject matter expert. Requires formal training/certification in software engineering and 5+ years of experience in data modeling, database design, data warehousing, data quality standards, and documentation. Preferred qualifications include experience with secure production code, APIs, Micro Services, Data Platforms, Data Streaming (Kafka, Flink, Apache Iceberg), AWS certifications, Snowflake, and Databricks.

What you'd actually do

  1. Drive data architecture decisions that impact product design, application functionality, and technical operations and processes.
  2. Collaborate with cross-functional teams to understand data needs and translate them into actionable solutions.
  3. Design and maintain data architecture frameworks that support business objectives and scalability.
  4. Map data requirements to downstream systems, facilitating efficient data flow and utilization.
  5. Develop and implement strategies for performing data completeness checks, ensuring data integrity and quality.

Skills

Required

  • software engineering concepts
  • data modeling
  • database design
  • data warehousing concepts
  • conceptual, logical, and physical data models
  • data integrity
  • data quality standards
  • data profiling
  • documentation for data models
  • mapping specifications
  • migration processes
  • system design
  • application development
  • testing
  • operational stability
  • communication skills
  • collaboration skills

Nice to have

  • secure, high-quality production codes
  • API's
  • Micro Services frameworks
  • Data Platforms
  • Data Streaming
  • Stream Processing techniques using Kafka, Flink, Apache Iceberg
  • AWS certification
  • Snowflake
  • Databricks

What the JD emphasized

  • data governance and regulatory standards