Finance Data and Insights Team - Data Domain Architect Lead

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

Lead Data Architect for a Finance Data & Insights team focused on transforming raw data into actionable insights for Consumer and Community Banking (CCB). Responsibilities include modernizing the data environment, streamlining data consumption, executing operational processes, identifying data issues, designing and delivering data products, and supporting migration and UAT. Requires experience in data analytics, architecture, financial reporting, BI tools, SQL, and data management. Preferred experience with big data tools, cloud data warehouses, and Gen AI tools.

What you'd actually do

  1. Contribute to the transformation and modernization of our data environment to serve the analytical and reporting needs of the Risk Weighted Assets Actuals reporting function
  2. Execute and take ownership of operational processes with an emphasis on accuracy and timeliness of meeting deliverables on prescribed timetables / calendars
  3. Identify hidden problems and patterns in data proactively and use those insights to drive process improvements
  4. Motivate and coach a highly skilled cross functional team to ensure optimal performance and consistent delivery against priorities and timelines
  5. Partner with the Technology Team to design and deliver data products that brings together essential data categories to enable the Finance function to support their analytical and reporting needs

Skills

Required

  • Bachelor’s degree in MIS, Computer Science, Finance, Accounting, or other related area with relevant work experience
  • 5+ years of experience in data analytics, architecture, or financial reporting systems
  • Experience with business intelligence analytics and data wrangling tools such as Alteryx, SAS, or Python
  • Experience with relational databases optimizing SQL to pull and summarize large datasets, report creation and ad-hoc analyses
  • Data Quality Management: Understanding of strategies and tools for data profiling, cleansing, and validation to maintain high data quality
  • Domain Knowledge: Deep understanding of the specific industry or business domain in which the organization operates
  • Demonstrated experience delivering process improvement or automation
  • Highly motivated, self-directed, curious to learn new technologies, strong team player
  • Strong analytical and problem-solving ability; Excellent written and verbal communication skills
  • Experience in reporting development and testing, and ability to interpret unstructured data and draw objective inferences given known limitations of the data
  • Strong knowledge and experience with data management, data lineage, data dictionaries, and making data discoverable

Nice to have

  • Experience with Hive, Spark SQL, Impala or other big-data query tools
  • Experience with modern gen AI tools such as ChatGPT, Genie, and/or Spotter
  • Strong knowledge and experience with data management, data lineage, data dictionaries, and making data discoverable
  • Experience with ThoughtSpot
  • AWS, Databricks, Snowflake, or other Cloud Data Warehouse experience
  • Hyperion Essbase cube design and administration experience
  • Experience eliminating user tools, saving time, and increasing ability to generate insights through data, dashboards, and developing new capabilities
  • Proficient user of the Microsoft Office Suite (primarily Excel)

What the JD emphasized

  • 5+ years of experience in data analytics, architecture, or financial reporting systems
  • Experience with business intelligence analytics and data wrangling tools such as Alteryx, SAS, or Python
  • Experience with relational databases optimizing SQL to pull and summarize large datasets, report creation and ad-hoc analyses
  • Data Quality Management: Understanding of strategies and tools for data profiling, cleansing, and validation to maintain high data quality
  • Domain Knowledge: Deep understanding of the specific industry or business domain in which the organization operates
  • Demonstrated experience delivering process improvement or automation
  • Strong knowledge and experience with data management, data lineage, data dictionaries, and making data discoverable