Associate Distinguished Engineer - Senior Data Leader

Nagarro•New York City, NY

6d•Hybrid

About The Position

We are looking for a senior data leader who has built enterprise data platforms, master data management and semantic layers at real scale — more than once — and who can sit across the table from client data leadership as a thinking partner in the morning and be in the modelling detail with the delivery team that afternoon. This is not an advisory role with a delivery team attached. It is a hands-on leadership role with a seat at the strategy table.

Requirements

15+ years in data, with the last several in senior architecture or data leadership roles.
At least two MDM programs taken to production, with genuine accountability for match, merge and survivorship decisions.
At least three enterprise data platform builds delivered end to end at large, complex organizations (multi-business-unit, multi-region, heterogeneous source estates).
Demonstrable experience designing and landing a semantic layer or shared business ontology that survived contact with more than one business unit.
Track record of making the case for foundation work to executive stakeholders and holding that sequencing when the pressure is to jump straight to use cases.
Experience in environments where data arrived through acquisition and accretion rather than design.
Deep, current, hands-on depth in Cloud Data Platform Snowflake (architecture, performance, cost, governance, data sharing).
Deep, current, hands-on depth in MDM Reltio in production, or equivalent enterprise MDM (Informatica, Stibo, Tamr) with a clear view on where Reltio fits.
Deep, current, hands-on depth in Governance & Catalog Collibra (catalog, lineage, policy, workflow, and how to drive adoption rather than shelfware).
Deep, current, hands-on depth in Data Quality Soda, Great Expectations or equivalent, implemented as enforced controls in the pipeline.
Deep, current, hands-on depth in Cloud AWS and Google Cloud (hands-on, both, with a view on when each is the right answer).
Deep, current, hands-on depth in Modelling & Pipelines (Dimensional and data-vault modelling, dbt, Orchestration, Streaming and batch).

Nice To Haves

Experience retiring legacy systems and explaining the process.
Experience resolving conflicting entity definitions between business owners.
Ability to explain technical concepts to a CFO.
Experience deferring use cases due to data readiness.
Ability to articulate reasons for faster subsequent data initiatives.

Responsibilities

Build enterprise data platforms, master data management, and semantic layers at scale.
Act as a thinking partner to client data leadership.
Engage in modeling details with the delivery team.
Take a hands-on leadership role with a seat at the strategy table.
Deliver enterprise data platform builds end to end at large, complex organizations.
Design and implement a semantic layer or shared business ontology.
Make the case for foundation work to executive stakeholders and manage sequencing.
Manage data arrival through acquisition and accretion.
Retire legacy systems (e.g., legacy warehouses, duplicate MDM stacks, reporting layers).
Land survivorship decisions when business owners define entities differently.
Explain the difference between a data catalog and a semantic layer to a CFO in terms of business impact.
Turn down or defer use cases when underlying data is not ready.
Improve the speed of subsequent data initiatives through learning and optimization.