Engineering Manager, Company Data - Grata

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.

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Job Description:

Grata is the leading private market dealmaking platform. We make it easy to find, research, and engage with private companies while powering end-to-endM&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 anEngineering Manager to leadone of our Data Product Pillars,ateam responsible for the systems and workflows that create, enrich,validate, and serve Grata's proprietary private-companydatasets. 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'sdata more comprehensive,accurate, fresh, and actionable for dealmaking 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 bothdelivery 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,identifyingand 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 forcompanyprofiles, financials,transactions,ownership, firmographics, and related market intelligence.

• Partnering closely with Product Managers and Data/AI partners toidentifycustomer 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 pipelines, data quality systems, and queue-based, event-driven, or asynchronous workflows.

• Strong grasp of data modeling, entity resolution, schema evolution, reliability, observability, architectural patterns, and engineering trade-offs.

• Proficiencywith AI-driven and agentic coding workflows: able to break down complex goals, provide context, delegate work to engineers and parallel agents, and verify output quality.

• Demonstrated ability to define what good looks like for data and software systems through clear acceptance criteria, evaluations, tests, metrics, and review practices.

• Outcome-oriented leadership: ability to connect technical and data investments to customer value, product strategy, and commercial outcomes while reinforcing strong ownership across the team.

Technical Experience (Nice to Have)

• Familiarity with modern data processing systems, such as:

• Databricks, Spark, or distributed data processing

• Kafka, Pulsar, or similar event streaming platforms

• Elasticsearch/OpenSearch, graph databases, or search/indexing infrastructure

• Experience with LLM-assisted data extraction, enrichment, classification, orevaluationworkflows.

• Experience with entity resolution, deduplication, taxonomy/ontology design, orknowledgegraph-style data models.

• Exposure tocloud-native architectures and scalable backend services.

What We’re Looking For

We'relooking for an engineering leader who brings strong judgment, ownership, and collaboration skills. You maydemonstratestrengths in areas such as:

• Anticipating cross-team constraints and balancing technical and data risk with delivery goals.

• Holding teams to a high-quality bar for both code and data while reinforcing sustainable execution.

• Forecasting capacity, negotiating scope, and planning effectively across quarters.

• Communicating clearly with technical and non-technical partners, especially when translating ambiguous data problems into actionable plans.

• Guiding teams through architectural evolution, platform upgrades, and data model changes.

• Proactively improving processes, metrics, engineering effectiveness, and data quality feedback loops.

• Developing engineers into product-minded, agent-first builders who canoperatewith autonomy, context, and end-to-end ownership.

The base salary range represents the estimated low and high end for this position based on a good faith assessment of the role and market data at the time of posting. Consistent with applicable law, each candidate’s compensation offer may vary and will be determined based on but not limited to, your geographic region, skills, qualifications, and experience along with the requirements of the position. This position may be eligible for bonuses, commissions, or overtime if applicable. Benefits include health insurance (medical, dental, vision), a retirement savings plan, paid time off, and other employee benefits. Specific details will be provided during the interview process. Datasite reserves the right to modify this pay range at any time.

Our company is committed to fostering a diverse and inclusive workforce where all individuals are respected and valued. We are an equal opportunity employer and make all employment decisions without regard to race, color, religion, sex, gender identity, sexual orientation, age, national origin, disability, protected veteran status, or any other protected characteristic. We encourage applications from candidates of all backgrounds and are dedicated to building teams that reflect the diversity of our communities.