Head of Data Warehousing

Forbes Advisor, part of the Forbes Marketplace family, provides consumers with
expert-written insights, news, and reviews on personal finance, health, business, and
everyday life decisions. We empower our audience with data-driven knowledge so
they can make informed choices confidently—balancing the agility of a startup with
the stability of a seasoned enterprise

Role Overview
The Head of Data Warehousing is a strategic, senior leadership role responsible for
setting the vision and direction of our data warehousing function. You will architect,
implement, and maintain a state-of-the-art data warehouse that drives actionable
insights across revenue, subscriptions, paid marketing channels, and operational
functions. Your leadership will ensure data quality, robust pipeline design, and
seamless integration with business intelligence tools. This role requires a strong mix
of technical acumen, team management, and cross-functional collaboration—
especially with teams focused on SEM, Digital Experiences, and revenue attribution

Key Responsibilities
Strategic Data Architecture & Pipeline Leadership
●Vision & Strategy:

○Define and execute the long-term strategy for our data warehousing
platform using medallion architecture (Bronze, Silver, Gold layers) and
modern cloud-based solutions.
●End-to-End Pipeline Oversight:
○Oversee data ingestion (via Google Ads, Bing Ads, Facebook Ads, GA,
APIs, SFTP, etc.), transformation (leveraging DBT, and SQL [via
BigQuery]), and reporting, ensuring that our pipelines are robust and
scalable.
●Data Modeling Best Practices:
○Champion best practices in data modeling, including the effective use
of DBT packages to streamline complex transformations.
Data Quality, Governance & Attribution
●Quality & Validation:
○Establish and enforce rigorous data quality standards, governance
policies, and automated validation frameworks across all data streams.
●Standardization & Visibility:
○Collaborate with the Data Engineering, Insights and BIOps team to
standardize data definitions (including engagement metrics and
revenue attribution) and ensure consistency across all reports.
●Attribution Focus:
○Develop frameworks to reconcile revenue discrepancies and unify
validation across Finance, SEM, and Analytics teams.
○Ensure accurate attribution of revenue and paid marketing channel
performance, working closely with SEM and Digital Experiences teams.
●Monitoring & Alerting:
○Implement robust monitoring and alerting systems (e.g., Slack and
email notifications) to quickly identify, diagnose, and resolve data
pipeline issues.
Team Leadership & Cross-Functional Collaboration
●People & Process:
○Lead, mentor, and grow a high-performing team of data warehousing
specialists, fostering a culture of accountability, innovation, and
continuous improvement.
●Stakeholder Engagement:

○Partner with RevOps, Analytics, SEM, Finance, and Product teams to align
the data infrastructure with business objectives.
○Serve as the primary data warehouse expert in discussions around
revenue attribution and paid marketing channel performance, ensuring
that business requirements drive technical solutions.
●Communication:
○Translate complex technical concepts into clear business insights for
both technical and non-technical stakeholders.
Operational Excellence & Process Improvement
●Deployment & QA:
○Oversee deployment processes, including staging, QA, and rollback
strategies, to ensure minimal disruption during updates.
●Continuous Optimization:
○Regularly assess and optimize data pipelines for performance,
scalability, and reliability while reducing operational overhead.
●Legacy to Cloud Transition:
○Lead initiatives to transition from legacy on-premise systems to
modern cloud-based architectures for improved agility and cost
efficiency.
Innovation & Thought Leadership
●Emerging Trends:
○Stay abreast of emerging trends and technologies in data warehousing,
analytics, and cloud solutions.
●Pilot Projects:
○Propose and lead innovative projects to enhance our data capabilities,
with a particular focus on predictive and prescriptive analytics.
●Executive Representation:
○Represent the data warehousing function in senior leadership
discussions and strategic planning sessions

Qualifications
Education & Experience

●Bachelor’s or Master’s degree in Computer Science, Data Science, Information
Systems, or a related field.
●8+ years of experience in data engineering, warehousing, or analytics roles,
with at least 3–5 years in a leadership capacity.
●Proven track record in designing and implementing scalable data
warehousing solutions in cloud environments.

Technical Expertise
●Deep experience with medallion architecture and modern data pipeline tools,
including DBT (and DBT packages), Databricks, SQL, and cloud-based data
platforms.
●Strong understanding of ETL/ELT best practices, data modeling (logical and
physical), and large-scale data processing.
●Hands-on experience with BI tools (e.g., Tableau, Looker) and familiarity with
Google Analytics, and other tracking systems.
●Solid understanding of attribution models (first-touch, last-touch, multi-
touch) and experience working with paid marketing channels.

Leadership & Communication
●Excellent leadership and team management skills with the ability to mentor
and inspire cross-functional teams.
●Outstanding communication skills, capable of distilling complex technical
information into clear business insights.
●Demonstrated ability to lead strategic initiatives, manage competing
priorities, and deliver results in a fast-paced environment.

Perks & Benefits
●Flexible/Remote Working: Enjoy flexible work arrangements in a collaborative,
distributed team culture.
●Competitive Compensation: Attractive salary, performance-based bonuses,
and comprehensive benefits.
●Time Off: Generous paid time off, parental leave policies, and a dedicated day
off on the 3rd Friday of each month.

If you are a visionary leader with a passion for building resilient data infrastructures,
a deep understanding of revenue attribution and paid marketing channels, and a
proven ability to drive strategic business outcomes through data, we invite you to
join our Data & Analytics team and shape the future of our data warehousing
function.