What are the responsibilities and job description for the Reporting, Insights, and Analytics Team - Data Domain Architect Lead position at JPMorgan Chase?
Join a team where you will lead the end‑to‑end architecture for FORCE Reporting, Insights & Analytics, own the FORCE data schema, enforce governance, and deliver a scalable, high‑performance lakehouse that powers advanced dashboards and analytics.
As Data Domain Architect Lead, within the Functions, Operations, Real Estate, Culture and Expenditure (FORCE) Reporting, Insights and Analytics Team, you will partner with Product, Technology, P&A, CFO, D&A, Controllers, and global teams to convert business needs into governed, resilient designs.
Job Responsibilities:
- Publish architecture roadmap and decisions; define medallion layering; standardize patterns and provide guidance on tuning Spark/Delta (partitioning, OPTIMIZE, ZORDER, caching) and orchestration for reliability.
- Normalize Unity Catalog, Delta Lake schema evolution, vacuum/auto‑compaction, and Databricks Workflows and enforce lineage/metadata, RBAC/ABAC, encryption, PII handling, DUC alignment.
- Convert requirements to designs, cross‑site design reviews, and shared documentation across geographies.
- Support manual‑file automation and post‑automation retirements and assist in NLQ pilots and in developing LLM‑assisted workflows.
- Run workshops; publish runbooks, coding standards, and architecture playbooks
- Partner with Product, Technology, P&A, CFO, D&A, Controllers, and global teams to convert business needs into governed, resilient designs. Mentor talent and tie delivery to measurable OKRs.
- 1 direct report and mentors broader architecture/modeling community
Required qualifications, capabilities, and skills:
- 10 years in data architecture/engineering; 5 years leading enterprise analytics architecture
- Expert Databricks/Spark/SQL and Delta Lake performance patterns (including partitioning, OPTIMIZE, ZORDER, caching, vacuum)
- Unity Catalog lineage/metadata, RBAC/ABAC, encryption, regulated‑industry governance
- Proven delivery of latency/cycle‑time targets at scale
- Experience integrating BI platforms (ThoughtSpot/Tableau/Sigma) into governed lakehouse ecosystems
- Stakeholder leadership, executive communication, and Agile delivery literacy
Preferred qualifications, capabilities, and skills:
- Python, PySpark, and SQL fluency; Databricks Workflows/Airflow
- FinOps/cost optimization such as NLQ and LLM‑assisted documentation
- Travel: 1%–10%