Engineering Manager, Company Data - Grata

Reposted 6 Hours Ago
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2 Locations
In-Office
141K-248K Annually
Senior level
Software
We empower dealmakers around the world with the tools they need to succeed across the entire M&A journey.
The Role
Lead and manage the engineering team owning Grata's proprietary company data. Oversee large-scale ingestion, entity resolution, search/indexing, pipeline reliability, data quality, and cross-functional delivery while coaching engineers and balancing short-term delivery with long-term technical health.
Summary Generated by Built In

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 dealmaking 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 an 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 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 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 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. 

  • Proficiency with 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, or evaluation workflows. 

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

  • Exposure to cloud-native architectures and scalable backend services. 
     

What We’re Looking For

We're looking for an engineering leader who brings strong judgment, ownership, and collaboration skills. You may demonstrate strengths 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 can operate with autonomy, context, and end-to-end ownership. 

#LI-Grata

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.

$141,000.00 - $248,000.00

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.

Skills Required

  • Experience leading engineering teams that build large-scale data processing or data platform systems.
  • Strong comfort with Python in a data-intensive, full-stack environment.
  • Experience designing and operating queue-based, event-driven, or asynchronous pipelines at scale.
  • Familiarity with entity resolution, record matching, deduplication, or data quality problems.
  • Proficiency with search and indexing systems such as Elasticsearch or equivalent.
  • Familiarity with Databricks or Spark-based pipelines.
  • Experience with Kafka, Pulsar, or similar event streaming platforms.
  • Experience with Airflow, dbt, or workflow orchestration tools.
  • Experience applying LLMs or ML to extraction, classification, or entity-matching problems.
  • Exposure to cloud-native architectures and scalable backend services.
  • Experience in private market intelligence, firmographics, or related data-product domains.

DataSite Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about DataSite and has not been reviewed or approved by DataSite.

  • Healthcare Strength Health coverage is described as comprehensive, including medical, dental, vision, mental‑health resources, and an employee assistance program. Feedback suggests these offerings align with mainstream expectations for mid‑size SaaS employers.
  • Retirement Support A 401(k) with employer match is consistently referenced, with some mentions of immediate vesting. Feedback suggests the retirement program is competitive relative to common market practices.
  • Leave & Time Off Breadth Paid time off is characterized as meaningful, including paid holidays, sick time, and generous PTO ranges, with certain business units citing unlimited PTO and notable parental leave. Feedback suggests time off is a valued and frequently cited strength.

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The Company
HQ: Minneapolis, MN
821 Employees
Year Founded: 1968

What We Do

Datasite the maker of Datasite Diligence virtual data room platform, helping dealmakers around the world close more deals faster.

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