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Engineering Manager, Company Data

Job in New York, New York County, New York, 10261, USA
Listing for: Grata
Full Time position
Listed on 2026-08-22
Job specializations:
  • Software Development
    Data Engineering
Salary/Wage Range or Industry Benchmark: 141000 - 248000 USD Yearly USD 141000.00 248000.00 YEAR
Job Description & How to Apply Below
Position: Engineering Manager, Company Data - Grata
Location: New York

Datasite and its associated businesses are the global center for facilitating economic value creation for companies across the globe. From data rooms to AI deal sourcing and more. Here you’ll find the finest technological pioneers:
Datasite, Blueflame AI, Grata, and Sherpany. They all, collectively, define the future for business growth.

Apply for one position or as many as you like. Talent doesn’t always just go in one direction or fit in a single box. We’re happy to see whatever your superpower is and find the best place for it to flourish. Get started now, we look forward to meeting you.

Job Description

Grata is the leading private market deal making platform. We make it easy to find, research, and engage with private companies while powering end-to-end M&A business development workflows
. Our platform delivers the most comprehensive, accurate, and searchable proprietary data on private companies, their financials, and their owners.

We are looking for a Engineering Manager to lead one of our Data Product Pillars, a team responsible for the systems and workflows that create, enrich, validate, and serve Grata's proprietary private‑company datasets. This role sits at the intersection of data engineering, product, AI‑enabled automation, and scalable platform engineering, and will play a critical role in making Grata's data more comprehensive, accurate, fresh, and actionable for deal making teams.

Grata is a hybrid company, with in-office collaboration in NYC on Mondays, Tuesdays, and Thursdays.

What You’ll Do

As an Engineering Manager, you will be accountable for both delivery and people leadership, while partnering closely with Product, Data, AI, Design, and customer‑facing stakeholders.

You Will
  • Own the outcomes of your team's efforts by ensuring successful data and product deliveries, including incremental value creation, data coverage, freshness, quality, system performance, and commercial impact.
  • Coach engineers on growth plans and promotions using established engineering pathways.
  • Establish and evolve healthy team practices, including planning, execution, quality, data validation, and operational excellence.
  • Represent Engineering in cross‑functional ceremonies and planning with Product, Data, AI, Design, Data Operations, and customer‑facing partners.
  • Balance near‑term delivery with long‑term technical health, identifying and managing data platform debt, schema evolution, pipeline reliability, and operational risk.
  • Translate product, data, and technical vision into clear execution plans, crisp task breakdowns, and measurable outcomes.
  • Teach and model effective delegation in an AI‑enabled engineering environment: give engineers and agents the right context, tools, constraints, and definition of good, then inspect outcomes.
  • Foster a culture of high ownership, psychological safety, and sustainable pace.

This role is primarily focused on management and leadership, with hands‑on technical engagement as needed to guide architecture, unblock teams, and support high‑impact data initiatives.

What You’ll Be Working On
  • Building and scaling Grata's proprietary company data platform, including ingestion, enrichment, normalization, entity resolution, quality controls, and serving layers.
  • Improving freshness, coverage, and accuracy for company profiles, financials, transactions, ownership, firmographics, and related market intelligence.
  • Partnering closely with Product Managers and Data/AI partners to identify customer pain points, automate data workflows, and turn messy sources into trusted product experiences.
  • Developing platform capabilities that make Grata's data more searchable, actionable, and defensible across M&A business development workflows.
  • Strengthening observability, evaluation, and incident response for data systems customers depend on.
Technical Requirements (Must Have)
  • Experience leading engineering teams that build data‑intensive products, proprietary datasets, or data platform capabilities at scale.
  • Strong comfort with Python, SQL, and backend services in a data‑heavy environment; ability to guide full‑stack/API work when data capabilities surface in the product.
  • Experience designing and operating ETL/ELT…
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