Director of Data

The Director of Data owns the company’s data platform, governed metrics, client identity resolution, data quality, privacy controls, and AI-ready datasets. This leader manages the data team, establishes governance and operating standards, oversees warehouse and pipeline architecture, and ensures reliable data for Finance, leadership, products, and ML/LLM systems. The role requires hands-on technical leadership, roadmap ownership, stakeholder communication, and accountability for data reliability, lineage, security, and platform costs. The summary above was generated by AI Role

Acquisition.com helps businesses scale. We hold data from thousands of client businesses, including company profiles, purchases, product usage, and live connections to bank, CRM, and advertising accounts. Our founders have said the company must be data-first before it can be AI-first. This role makes that true.

We are hiring our first Director of Data, the first leader solely accountable for the data function. Three Senior Data Engineers and a half-time analyst run the warehouse, single-client-record pipelines, and reporting used by Finance and Leadership, supporting two client-facing products in daily use. What is missing is one owner for accurate numbers, one reliable client record, AI-ready data, and one data program.

The mandate is to make data reliable and usable by people, products, and AI systems. You own the data platform, single client record, governed business metrics, and data used to train, evaluate, and ground AI systems. You lead the team and data quality program while remaining hands-on enough to write SQL, inspect models, and diagnose failures. You report to the CTO; Platform owns infrastructure and application engineering; AI Engineering owns model architecture and runtime; and you own the data those systems train on, evaluate against, and retrieve from. The existing team reports to you on day one, and you set the standards every data-producing team must meet. Responsibilities

• Own the data platform end to end, including the warehouse, ingestion, transformation, semantic layer, orchestration, observability, vendors, and cost.
• Build the governed data systems behind production ML and LLM products, including versioned training, evaluation, feature, and retrieval datasets, embeddings and vector indexes, and controls for labeling, lineage, leakage, drift, and retrieval quality.
• Establish one authoritative client record across source systems with identity resolution, field-level provenance, and enforceable data contracts.
• Create the governed metrics layer and data quality program that Leadership and Finance use, including one definition per metric, published freshness standards, automated reconciliation, and named ownership by domain.
• Enforce privacy and access controls in the data layer with Security and Legal, including retention, deletion, cataloging, lineage, and boundaries between operating companies and partners.
• Lead the data team as one program through a published roadmap, clear operating cadence, documented on-call, talent development, and hands-on technical leadership when the work requires it., * Within 60 days, publish one data roadmap, review it monthly with the CTO and quarterly with the founders, and assign an owner to every data initiative.
• AI assistants answer the top 20 leadership metric questions; every AI product has a team-owned evaluation set; and no model ships without testing it with AI Engineering.
• The client record covers every active client, core fields are at least 95% complete, connected-source data uses the same model, and every material field has provenance.
• Every executive KPI and Finance statement uses governed metrics; reconciliation runs weekly; unmatched payment volume falls below 1% from $9.8 million; and critical failures are detected within one hour and resolved within one business day.
• Retention and deletion are automated, deletion requests complete within 45 days with an audit record, and warehouse access is reviewed quarterly.
• Every data engineer has a level, growth plan, and on-call; no critical pipeline depends on one person; and platform spend and unit cost are reported monthly.

Schedule

• Full-time, standard Pacific Time business hours, Monday through Friday.
• Flexibility to support security incidents and critical business needs., Leads approximately 35 engineers across data engineering, integration engineering, and integration support. Owns delivery predictability, manager development, operational reliability, SLA performance, data platform modernization, integration scalability, and organizational clarity. Partners with product, data science, commercial, and delivery teams while overseeing healthcare integrations with EHR systems, enterprise data infrastructure, incident management, and client-facing reliability commitments. Top Skills: Ai/MlAthenaCernerEhrEltEpicETLFhirHl7Medallion Architecture Optum

Associate Director - QOI Supplemental Data Operations - Remote CST or EST

7 Days Ago In-Office or Remote 113K-193K Annually Mid level 113K-193K Annually Mid level Artificial Intelligence * Big Data * Healthtech * Information Technology * Machine Learning * Software * Analytics Leads governance, implementation, validation, audit readiness, and optimization of clinical supplemental data sources supporting HEDIS, CMS, and state quality reporting. Manages analyst teams, collaborates with clinical, technology, operational, vendor, and audit stakeholders, translates requirements into technical specifications, drives data quality and compliance improvements, and serves as the enterprise liaison to HEDIS auditors. Develops action plans, oversees source audits, supports executive communications, and manages complex projects and reporting initiatives. Top Skills: AdtCcdFhirHl7Microsoft AccessExcelMicrosoft OutlookMicrosoft PowerpointMicrosoft VisioMicrosoft WordOruSQL

What you need to know about the Colorado Tech Scene

With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.

Key Facts About Colorado Tech

• Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
• Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
• Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
• Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
• Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
• Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute

• 8+ years of data engineering, analytics engineering, or data platform experience, including leading a data function and directly managing senior engineers; experience as a company’s first or primary data leader is preferred.
• Hands-on experience building or rebuilding a modern cloud data stack, with advanced SQL skills and practical experience with warehouse architecture, data modeling, transformation, orchestration, and observability.
• Experience owning data systems used by production ML or LLM products, including versioned training, evaluation, and retrieval datasets, embeddings and vector search, labeling, leakage prevention, drift monitoring, and retrieval-quality evaluation. Must be able to explain how data quality decisions affected model performance in production.
• Experience building a customer master or identity resolution model across multiple source systems, including matching logic, survivorship rules, and field-level provenance.
• Experience delivering governed business metrics used by executives and Finance, including automated reconciliation, published data-quality standards, clear remediation ownership, and the ability to explain data tradeoffs in plain language.
• Experience implementing data governance and privacy controls, including retention, deletion, lineage, role-based access, and working knowledge of CCPA and CPRA; financial transaction or multi-entity data experience is preferred., Be at your best when your best is needed. Enjoyment of a hard challenge. Those who have the drive to constantly improve, the superior intellect and long term commitment to see incremental improvements become compounding returns. Sincere Candor

Have the self awareness to accurately perceive and communicate hard truths that improve others and self, the courage to do so, and the humility to accept them, even when it hurts. Nothing great can be built without feedback: internally or externally. Unimpeachable Character

Be the type of person with whom people are always proud to associate, personally and professionally. We look for true alignment of thoughts, words, and actions towards a goal worth pursuing.

• The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below)., We offer a comprehensive, evolving benefits package designed to support your health, family, and wellbeing. Some key offerings:
• Flexible Unlimited Paid Time Off and Company-wide Holidays
• Employer sponsored Medical, Dental, & Vision plans
• $1,950 annual Employer HSA contribution
• FSA options including dependent care
• Employee assistance program and mental health resources
• Employer match program for 401(k), eligible for both Traditional and Roth accounts
• $1,200 annual wellness reimbursement through JOON that supports health, family care, pet care, fitness, and more!

• For local or visiting team members, enjoy access to a state of the art gym at our HQ in Las Vegas

• Benefits eligibility applies only to full-time exempt roles.

ACQ Core Values:

Our core values are the heart and soul of this incredible company. The right person for this role will appreciate each of these values, personally subscribe to them, and understand why each is critical to having a great business. Competitive Greatness, 4 Days Ago Remote or Hybrid 245K-335K Annually Expert/Leader 245K-335K Annually Expert/Leader Fintech * Machine Learning * Payments * Software * Financial Services Leads data science for consumer and developer experiences, partnering with engineers and product managers to deliver customer-focused products. Builds, evaluates, validates, and deploys machine learning models using large-scale numerical and textual data. Applies statistical modeling, A/B testing, clustering, classification, sentiment analysis, time series, and deep learning while translating technical insights into business outcomes. The role also includes team leadership, talent development, and evaluating emerging AI and cloud technologies. Top Skills: SparkAWSCondaGenerative AiH2OMachine LearningPythonRRelational DatabasesScala Cedar