Own and lead analytical data product definition, adoption, and lifecycle management on the Target State data Platform. Act as a senior bridge between business domains, Data Engineering, Platform Engineering, and Architecture to ensure complex enterprise datasets are translated into trusted, well‑defined, and consumption‑ready data products supporting analytics, reporting, and downstream use cases across Core Reference, IBOR, Datahub, Stamford Data Warehouse, and many other data initiatives.

Key Responsibilities

• Lead definition and ownership of analytical data products, including scope, business semantics, metrics, and consumption expectations

• Translate complex business requirements into clear data definitions, KPIs, and analytical specifications

• Partner with Data Engineering teams to design, validate, and evolve curated analytical datasets and semantic / serving models

• Ensure consistency of metric definitions and business logic across BI tools and downstream consumers

• Define data product contracts including schemas, documentation, SLAs, freshness, and quality expectations

• Drive implementation and review of data quality rules, reconciliation checks, and acceptance criteria

• Support data lineage, certification, and discoverability through collaboration with Platform Engineering and catalog teams

• Perform impact analysis and coordinate communication for schema, metric, or semantic changes

• Act as the primary senior analytics point‑of‑contact for business stakeholders and data consumers

• Mentor Data Product Analysts and promote data‑as‑a‑product best practices across teams

Qualifications

• Strong experience in data product, analytics, or senior data analysis roles, working closely with data engineering teams

• Advanced SQL skills and deep understanding of analytical query patterns

• Strong understanding of data modeling concepts, including curated analytical and semantic models

• Hands‑on experience with Snowflake and/or Databricks for analytical workloads

• Proven ability to translate business concepts into precise, consumable data definitions

• Strong communication skills across technical and business audiences

• Familiarity with data catalogs and metadata systems (Unity Catalog, Polaris, Horizon) preferred

• Familiarity with lakehouse concepts and open table formats such as Apache Iceberg is a plus

• Financial or enterprise data platform background preferred but not required