Engineering Manager (Company Data, Grata)

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 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 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 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 Benefits Culture and benefits built around work‑life balance Extensive resources to support physical and mental health Employee assistance program Generous retirement plans Incentives for referring new colleagues Learning, training and mentoring programs Cross‑functional projects Stretch assignments to help you progress Receive feedback and earn bonuses from peers & managers Employee bonding activities ESG and charitable team initiatives Requirements Strong grasp of data modeling, entity resolution, schema evolution, reliability, observability, architectural patterns, and engineering trade‑offs Experience leading engineering teams that build data‑intensive products, proprietary datasets, or data platform capabilities at scale Demonstrated ability to define what good looks like for data and software systems through clear acceptance criteria, evaluations, tests, metrics, and review practices Experience designing and operating ETL/ELT pipelines, data quality systems, and queue‑based, event‑driven, or asynchronous workflows 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 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 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 Kafka, Pulsar, or similar event streaming platforms Experience with entity resolution, deduplication, taxonomy/ontology design, or knowledge graph‑style data models Elasticsearch/OpenSearch, graph databases, or search/indexing infrastructure Experience with LLM‑assisted data extraction, enrichment, classification, or evaluation workflows Databricks, Spark, or distributed data processing Forecasting capacity, negotiating scope, and planning effectively across quarters Developing engineers into product‑minded, agent‑first builders who can operate with autonomy, context, and end‑to‑end ownership Communicating clearly with technical and non‑technical partners, especially when translating ambiguous data problems into actionable plans Holding teams to a high‑quality bar for both code and data while reinforcing sustainable execution Anticipating cross‑team constraints and balancing technical and data risk with delivery goals Exposure to cloud‑native architectures and scalable backend services Guiding teams through architectural evolution, platform upgrades, and data model changes Proactively improving processes, metrics, engineering effectiveness, and data quality feedback loops #J-18808-Ljbffr Socket.dev