Head of Data

Jobgether SRL; United States; Remote; USD 150,000 - 250,000; Full time

Benefits offered by this job

Remote work within the United States

Leadership opportunity to shape data

Cross-functional collaboration

Autonomy in data stack

Direct impact on revenue and ops

Job summary

Jobgether SRL is seeking a seasoned data leader in the United States to own the data strategy, governance, and analytics program. You will lead a small team and work closely with executive leadership to translate insights into revenue, cost, and operational decisions.

The role requires hands-on SQL, cloud data warehousing, dbt, and Dataform, plus a proven track record of delivering measurable business impact in attribution and data infrastructure improvements.

Qualifications

• Eight years of experience in data or analytics with leadership experience.
• Hands-on SQL and cloud data warehouse work within the past two years.
• Proficient in building data models with dbt or Dataform and maintaining pipelines.
• Regular use of AI tools in data work with quality controls.
• Demonstrated ability to influence revenue, profitability, or costs with measurable outcomes.
• Experience with build-versus-buy decisions and cost-reduction efforts.
• Strong executive communication to align data initiatives with business priorities.
• Ability to turn complex analyses into actionable insights for leadership.
• Broad tech versatility across analytics, governance, and data infra.

Responsibilities

• Own the data strategy and roadmap, prioritizing initiatives by impact on revenue, costs, risk, and ops.
• Establish intake, evaluation, and prioritization processes for data requests and communicate trade-offs to leadership.
• Lead development and maintenance of data warehouse, pipelines, and transformations using GCP, BigQuery, and Dataform.
• Oversee dashboards, reporting infra, and analytic solutions to support data-driven decisions.
• Develop reliable measurement and attribution capabilities, including server-side tracking with Marketing.
• Ensure customer segmentation, lifecycle analytics, and email performance metrics support retention and revenue.
• Implement data quality controls and governance to protect data integrity.
• Partner with Finance to reconcile orders and revenue across systems and improve reporting consistency.
• Evaluate tech stack and make build-vs-buy decisions to improve cost efficiency.
• Create a trusted semantic layer with consistent business metrics for dashboards and AI tools.
• Translate analytical findings into clear recommendations used by CEO and senior leaders.
• Lead a small analytics and data engineering team with hands-on SQL and data modeling.

Skills

8+ years data/analytics

Advanced SQL

Executive communication

Influence decisions

Build-versus-buy decisions

Data modeling

AI tooling

Leadership

Regulatory awareness

Tools

dbt

Dataform

BigQuery

Google Cloud Platform

Data pipelines

Job description

Accountabilities

• Own the data strategy and roadmap, prioritizing initiatives according to their expected impact on revenue, costs, risk, and operational performance.
• Establish clear processes for intake, evaluation, and prioritization of data requests, communicating trade-offs, capacity, and priorities to leadership and the team.
• Lead the development and maintenance of the data warehouse, pipelines, and transformation models, including Google Cloud Platform, BigQuery, Dataform, and associated ingestion tools.
• Oversee dashboards, reporting infrastructure, and analytical solutions that help teams make informed, data-driven decisions.
• Develop and maintain reliable measurement and attribution capabilities, including in-house attribution models, incrementality testing, and server-side conversion tracking in collaboration with Marketing.
• Ensure customer segmentation, lifecycle analytics, and email performance analysis support customer retention and revenue growth.
• Establish robust data quality controls to identify inconsistencies and prevent inaccurate information from reaching reports, dashboards, and business decisions.
• Implement data access policies and governance frameworks that protect sensitive customer information and define appropriate permissions for employees and AI agents.
• Partner with Finance to reconcile orders and revenue across e-commerce, ERP, and financial systems while improving inventory aging analysis, demand planning, and reporting consistency.
• Evaluate the data technology stack, making defensible build-versus-buy decisions and consolidating or eliminating tools where doing so improves cost efficiency and operational performance.
• Establish a trusted semantic layer and certified business metrics so that dashboards, analysts, and internal AI-powered data tools use consistent definitions and reliable figures.
• Work closely with the CEO and senior leadership to translate analytical findings into clear recommendations that influence revenue, spending, and cost decisions.
• Lead and develop a small team spanning analytics, data engineering, and analysis, while remaining actively involved in SQL, data modeling, code review, and technical problem-solving.
• Integrate AI-assisted development tools into daily workflows, maintaining appropriate review processes, security controls, and safeguards for production data.

Requirements:

• At least eight years of experience in data or analytics, including three or more years leading a data function or team.
• Recent hands-on experience writing SQL and working with a modern cloud data warehouse within the past two years.
• Proven experience building data models using dbt, Dataform, or a comparable transformation framework, along with developing and maintaining data pipelines.
• Regular, practical use of AI tools in data work, including AI-assisted coding and code review, supported by appropriate quality checks and access controls.
• Demonstrated ability to influence business decisions related to revenue, profitability, or costs, with measurable outcomes that can be clearly explained and quantified.
• Experience making strategic build-versus-buy decisions and reducing technology or infrastructure costs with demonstrable savings.
• Strong executive communication skills, including the ability to manage stakeholder expectations, explain trade-offs, and align data initiatives with business priorities.
• Ability to turn complex analyses into concise recommendations, clear visualizations, and actionable insights that leadership can use.
• Broad technical versatility across analytics, experimentation, attribution, reporting, data infrastructure, and governance.
• Strong analytical reasoning and a first-principles approach to unfamiliar problems, with the ability to challenge assumptions and identify practical solutions.
• A hands-on leadership style, combining team development and strategic direction with direct technical contribution.
• Nice to have: Experience in regulated industries such as hemp, cannabis, alcohol, or supplements, particularly where advertising, tracking, and attribution are affected by regulatory constraints.
• Nice to have: Experience in e-commerce, direct-to-consumer (DTC), or other consumer-focused businesses.
• Nice to have: Familiarity with Shopify event tracking, particularly for headless storefronts.
• Nice to have: Experience with identity resolution, marketing attribution, marketing mix modeling (MMM), or incrementality testing.
• Nice to have: Experience with semantic-layer technologies such as Cube and cloud platforms such as Google Cloud Platform.
• Nice to have: Experience working with Finance data, including revenue reconciliation, inventory management, and demand planning.

Benefits:

• Base salary: Annual range of $150,000–$250,000 USD .
• Remote work: Remote position within the United States, with a preference for candidates based in New York, San Francisco, or Los Angeles.
• Leadership opportunity: Own the data function end to end and shape its strategy, infrastructure, governance, and operating model.
• Business impact: Directly influence revenue growth, profitability, marketing investment, inventory planning, and operational efficiency.
• Technical ownership: Opportunity to shape the data technology stack, evaluate emerging AI tools, and make strategic build-versus-buy decisions.
• Cross-functional collaboration: Work closely with executive leadership, Finance, Marketing, Operations, and sales-channel teams.
• Team leadership: Lead a small, multidisciplinary data team while maintaining hands-on involvement in technical and analytical work.
• Innovation and autonomy: Help build scalable data capabilities in a growing business operating in a complex and evolving regulatory environment.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.