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Remote Head Of Data & Analytics Jobs (NOW HIRING)

A2Z Sync

Head of Data Platform

Englewood, CO · On-site +1

$63 - $81/hr

Analytics: Glue Data Catalog, Athena, QuickSight or equivalent BI layer. Hands-On Expectations This ... or Head-of role. * Deep experience with both relational (MySQL/PostgreSQL/Aurora) and NoSQL ...

A2Z Sync

Head of Data Platform

Englewood, CO · Remote

$65.25 - $84/hr

Analytics: Glue Data Catalog, Athena, QuickSight or equivalent BI layer. Hands-On Expectations This ... or Head-of role. * Deep experience with both relational (MySQL/PostgreSQL/Aurora) and NoSQL ...

RightMove Health

Director of Data & Analytics

About the Role RightMove Health is seeking a Director of Data & Analytics to own our analytical function as we scale into launch and beyond. This is a hands-on leadership role for someone who takes ...

Binance

Head of Data Science/AI

The Mission As Binance's Global Head of AI , you will architect and lead the intelligence layer of ... analyzing resumes, or assessing responses. These tools assist our recruitment team but do not ...

360training

Head of Analytics

This is a remote position, and we are looking to hire in the following states: AZ, FL, GA, LA, NJ ... Leverage data and information to fundamentally alter outcomes for the business * Help evaluate and ...

360training

Head of Analytics

There is NO VISA Sponsorship for this role This is a remote position, and we are looking to hire in ... Leverage data and information to fundamentally alter outcomes for the business * Help evaluate and ...

POLYWOOD

VP of Data & Analytics

Job Type Full-time Description POLYWOOD Hybrid / Remote Reports To: Chief Digital Officer The ... The Role The VP of Data & Analytics is POLYWOOD's senior data leader, responsible for the people ...

Atos

Head of AI

OR · On-site +1

Reports to: Head of Data & AI - North America * Direct reports: AI practice leadership team ... Geography: United States and Canada (remote/hybrid depending on location) * Travel: Up to 25-40 ...

Atos

Head of AI

OR · On-site +1

Reports to: Head of Data & AI - North America * Direct reports: AI practice leadership team ... Geography: United States and Canada (remote/hybrid depending on location) * Travel: Up to 25-40 ...

Newsela

Educational Data Analyst

$110K - $120K/yr

This role will report to the Head of Data Science. Why you'll love this role: * Engage with school ... We are a fully remote company. We provide a monthly tech stipend to support your WFH needs!

Libsyn

Head of Business Analytics

Head of Business Analytics Reports to: CEO Location: Remote, USA About Libsyn Libsyn (Liberated ... Libsyn's data spans multiple internal systems and third-party vendors. This role requires comfort ...

Method Financial

Head of Data Strategy & Access

New York, NY · On-site +1

$240K - $280K/yr

About the role We're hiring a Head of Data Strategy & Access to own Method's most consequential and technically complex external partnership effort. You'll be responsible for negotiating and securing ...

Slate Auto

Head of Planning & Analytics

Head of Planning & Analytics Department: Sales | Reports To: VP of Sales / Head of Sales | Level ... Establish data standards and governance frameworks to maintain data integrity across all sales and ...

Two95 International Inc.

Head of Marketing

Head of Marketing Location: 100% Remote work Job Type: Full time (Permanent with our client) Salary ... Extensive knowledge in market research and data analytics methods * Solid experience in different ...

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Remote Head Of Data Analytics information

What are some common challenges faced by a Remote Head of Data & Analytics, and how can they be addressed?

A Remote Head of Data & Analytics often faces challenges such as fostering team collaboration across time zones, ensuring data security, and maintaining alignment with business goals. Effective communication tools, regular virtual meetings, and clear documentation help bridge geographic gaps. Additionally, implementing robust data governance policies and close collaboration with IT and business stakeholders are essential for success. By prioritizing transparency and proactive problem-solving, remote leaders can build high-performing, cohesive data teams.

What are the key skills and qualifications needed to thrive as a Remote Head Of Data & Analytics, and why are they important?

To thrive as a Remote Head Of Data & Analytics, you generally need extensive experience in data strategy, advanced analytics, and leadership, often supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as SQL, Python, data visualization platforms (e.g., Tableau, Power BI), and big data frameworks, along with knowledge of data governance and cloud platforms, is typical, as are relevant certifications like Certified Analytics Professional (CAP). Outstanding communication, strategic thinking, and the ability to inspire and manage remote teams are crucial soft skills that set exceptional leaders apart. These competencies are vital for driving data-driven decision-making, fostering innovation, and ensuring effective collaboration across distributed teams.

What does a Remote Head of Data & Analytics do?

A Remote Head of Data & Analytics is responsible for overseeing an organization's data strategy, analytics initiatives, and data-driven decision-making processes, all while working remotely. This role involves managing teams of data professionals, defining key metrics, ensuring data quality, and leveraging analytics to support business goals. They collaborate with other departments to identify opportunities for data use, set best practices, and ensure compliance with data regulations. The remote aspect allows them to lead and coordinate teams from various locations using digital tools.
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Infographic showing various Remote Head Of Data & Analytics job openings in the United States as of June 2026, with employment types broken down into 5% Internship, 57% Full Time, 4% Part Time, 20% Temporary, 2% Contract, and 12% Nights. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution.
Head of Data Platform

Head of Data Platform

A2Z Sync

Englewood, CO • On-site, Remote

$63 - $81/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago

Job description

Why This Role Exists
We operate a multi-tenant automotive SaaS platform serving thousands of dealer groups across the United States. Our data layer - MySQL, Aurora, DynamoDB with DynamoDB Streams, S3, Glue Data Catalog - has grown to support a complex, high-throughput transactional platform. That layer works. Now we need to make it intelligent.
We are building a Dealer Intelligence Platform: a closed-loop system that observes raw signals from dealer operations, predicts outcomes, optimizes decisions under constraints, acts through approved channels, and learns from what happened. Pricing optimization, lead routing, inventory mix planning, service bay scheduling - each is a self-contained optimization function that consumes features, scores predictions, and closes the loop with action telemetry.
This role owns the entire data substrate that makes that loop possible - the lake, the feature store, the model registry, the action ledger, and the governance framework that keeps it all tenant-isolated and audit-grade. You are not inheriting a finished architecture; you are designing the one that turns a transactional platform into a decision engine.
Scope & Scale
  • Targeting 5,000+ dealer tenants, each with isolated databases and per-tenant configuration.
  • Billions in annual Gross Merchandise Value (GMV) flowing through platform transactions.
  • 30+ third-party integrations across DMS, CRM, lending, F&I, and marketplace providers - each pushing data in different formats (SOAP/XML, REST, JSON, email).
  • Data pipelines spanning 6 integration domains with multi-protocol vendor connectivity.
  • Data Streams processing real-time change events across onboarding, inventory, and transaction tables.
  • A Product roadmap with 6+ optimization functions - each requiring its own entity model, feature set, constraint definition, and feedback path.
What You Will Own
  • The data platform end to end: Bronze (raw + telemetry), Silver (canonical entities via Standardization Agent), Gold (KPIs + derived features) - plus the Feature Store and Action Ledger that make the optimization loop possible.
  • Feature Store architecture - online (sub-50ms reads for real-time scoring) and offline (point-in-time joins for training). Feature contract: owner, freshness SLO, PII tag, training/inference parity. Governed by Lake Formation.
  • Action Ledger - every recommendation, approval, override, and outcome logged as a first-class object. This is the substrate that closes the loop: without it, models cannot retrain, we cannot attribute lift, and we cannot prove value to dealers.
  • Model data pipeline - the feature materialization, training data assembly, and serving infrastructure that feeds SageMaker models and Bedrock agents across all optimization functions.
  • Data migration strategy for the legacy platform - defining which tables move to DynamoDB, which consolidate into Aurora Serverless, and how dual-write validation works at every stage.
  • Data quality and anomaly detection - automated monitoring for schema drift, null-rate spikes, stale pipelines, and integration data inconsistencies. If a bad feature reaches a model, that is your bug.
  • Data governance: retention policies, PII handling, audit trail integrity, and multi-tenant AI governance (per-dealer data isolation for model training, cost attribution for Bedrock inference, FTC-grade action audit).
  • Streaming and event-driven data flows: DynamoDB Streams, EventBridge, CDC patterns, and real-time feature materialization.
Technical Environment
  • Data Stores: DynamoDB (single-table design, DynamoDB Streams), MySQL/Aurora, S3 data lake (Bronze/Silver/Gold layers, Iceberg), DAX, Glue Data Catalog.
  • Feature Store: SageMaker Feature Store (online + offline), S3 + Iceberg for point-in-time training data, Lake Formation-governed feature access.
  • Streaming & Events: DynamoDB Streams, EventBridge, CDC, real-time feature materialization pipelines.
  • ML/AI Platform: SageMaker (training pipelines, model registry, Model Monitor), AWS Bedrock (Claude, Titan), LangChain/LangGraph, Bedrock Knowledge Bases.
  • Pipelines: Apache NiFi (multi-provider normalization), AWS Glue (ETL, Data Catalog), Athena (ad-hoc analytics).
  • Infrastructure: CloudFormation, Lake Formation, OpenTelemetry, CircleCI.
  • Analytics: Glue Data Catalog, Athena, QuickSight or equivalent BI layer.
Hands-On Expectations
This is not a slides-and-meetings role. We expect roughly 30-40% of your time in code and SQL (writing critical-path feature pipelines, data migrations, schema designs, and reviewing PRs with rigor), 40-50% in design (data architecture docs, entity modeling sessions, feature catalog design, optimization-function data contracts), and 10-20% on cross-team alignment, mentoring, and operating mechanisms.
First 12 Months
  • Months 1-3: Immerse in the data landscape - audit every data store, pipeline, integration flow, and DynamoDB Stream. Map the current entity model against the v2 optimization-function requirements. Publish the first data architecture ADR. Identify the top data quality gaps and define the canonical entity schemas that Silver and Gold will standardize around.
  • Months 4-6: Stand up the Feature Store (online + offline) and migrate the first round of features from Gold derivations. Build the Action Ledger schema and approval-gateway integration. Deliver the first data migration wave with dual-write validation. Ship automated data quality monitoring that catches drift before it reaches a model.
  • Months 7-9: Pricing Optimizer data pipeline live in production - features flowing, predictions scoring, action telemetry closing the loop. Feature catalog operational with freshness SLOs and PII tagging. Per-dealer + global model training pipelines running. Lead Routing data contracts defined and in shadow mode.
  • Months 10-12: Second optimization function (Lead Routing or Inventory Mix) in production. Drift detection and auto-rollback wired into Model Monitor. Outcome dashboards proving incremental lift to dealers. Data platform roadmap documented for the next 12 months. The team treats feature quality, action telemetry, and training/inference parity as non-negotiable engineering standards because of the patterns you set.

Requirements
You Should Have
  • 7+ years in data engineering or data architecture with at least 2 years in a platform-level architect or Head-of role.
  • Deep experience with both relational (MySQL/PostgreSQL/Aurora) and NoSQL (DynamoDB, DynamoDB Streams) data modeling - and strong opinions on when each is appropriate.
  • Hands-on experience building or operating feature stores - online serving, offline training, point-in-time correctness, feature freshness SLOs.
  • Hands-on experience with AWS data and ML services: Glue, Athena, S3, DynamoDB, DynamoDB Streams, Aurora, Lake Formation, SageMaker.
  • Current, practicing AI/Gen-AI practitioner - you have built or operated systems that prepare data for LLMs, embeddings, or ML models in production. This is not theoretical interest; it is hands-on recent experience.
  • Experience with streaming and CDC patterns: DynamoDB Streams, Kinesis, EventBridge, or Kafka for real-time data propagation and feature materialization.
  • Experience with data pipeline orchestration: NiFi, Airflow, Step Functions, or equivalent.
  • Understanding of data migration patterns: dual-write, change data capture (CDC), reconciliation validation, zero-downtime cutover.
  • Experience with multi-tenant data architectures - database-per-tenant, schema-per-tenant, Row-Level Security, and the judgment to know which trade-offs matter at 5,000+ tenants.
  • Strong data governance instincts: retention policies, PII handling, audit trails, cost attribution, and the discipline to enforce them before the first model ships.
  • The ability to write a data architecture doc that engineers can implement without ambiguity, and the judgment to know when to write the SQL or pipeline code yourself instead.
Strongly Preferred: ML & Optimization Data Infrastructure
  • Hands-on experience with SageMaker - training pipelines, model registry, Model Monitor, and production model lifecycle (shadow → canary → drift watch → auto-rollback).
  • Hands-on experience with AWS Bedrock - Knowledge Bases, model invocation, guardrails, and production deployment of foundation models.
  • Experience building embeddings pipelines - vectorizing structured and unstructured data for semantic search, recommendations, or retrieval-augmented generation.
  • Experience designing retrieval systems - chunking strategies, metadata filtering, re-ranking, and evaluating retrieval quality.
  • Experience building closed-loop data systems - action telemetry, outcome attribution, A/B holdout management, and lift measurement.
  • Experience with data quality and anomaly detection at scale - automated monitoring for schema drift, null rates, freshness SLAs, and feature/training skew.
  • Understanding of multi-tenant AI governance: PII redaction, tenant-scoped inference, per-dealer model routing, cost attribution, and audit logging.
Nice to Have
  • Experience with automotive, fintech, or multi-tenant marketplace data - compliance retention requirements.
  • Familiarity with data formats and protocols from third-party providers (CDK, DealerTrack, Tekion).
  • Experience with constrained optimization, assignment problems, or scheduling solvers at the data layer.
  • Background with event-driven and streaming data architectures (EventBridge, DynamoDB Streams, Kafka, CDC streams).
  • Experience with vector databases (OpenSearch, Pinecone) for production AI workloads.
  • Experience with Iceberg, Delta Lake, or other open table formats for lakehouse architectures.

Benefits
About A2Z Sync
A2Z Sync is a fast-paced and innovative automotive SaaS company seeking to make life better for our customers. We offer you a fun, casual, and collaborative culture, while fostering an environment where you work hard, see your results, and feel your impact. We are committed to our employees, and this starts with providing benefits that allow you to care for you and your family.
Mission
At A2Z Sync, we replace the friction of disconnected systems with the velocity of a single platform. We integrate digital insights with in-store operations to deliver transparent transactions that bring clarity to the car buyer and increased profitability to the dealer.
Our Values: We Are DRIVEN
  • Dealership Obsessed: We measure our success by the dealer's wins and the trust of their buyers, not just our own code.
  • Relentless Ownership: No lone wolves, but no pass-backs either. We don't say "that's not my job."
  • Invent with Purpose: We don't chase "shiny" tech. We replace guesswork with intelligence, building the "data backbone" that turns raw information into a competitive advantage.
  • Value Every Perspective: We are Better Together. We check egos at the door.
  • Evolve or Evaporate: Change is our constant. We stay ahead by learning faster than the competition.
  • Now Over Next: Perfection is the enemy of progress. We prefer action over endless analysis.
Here's how we are doing it:
  • A2Z Sync offers comprehensive medical, dental, and vision benefits.
  • Employer provided STD/LTD and life insurance.
  • Matching 401k plan.
  • Unlimited paid time off, including 10 paid holidays.
  • Real ownership of a high-stakes AI surface - your roadmap, your architecture decisions, your metrics.
  • The expected salary range for this role is $160,000 to $195,000 annually, commensurate with experience and qualifications.

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