Analytics Engineer

Fetch • Reston, VA

3h • $149,523 - $175,909 • Remote

About The Position

Fetch is at a major inflection point. With a rich dataset encompassing over $100B in deterministic, item-level consumer purchase data, we are strategically shifting to scale our data monetization efforts and build a suite of world-class data products. Our vision is for Fetch data to power every activation decision in the advertising ecosystem, directly or indirectly.
We are seeking a Analytics Engineer to be a technical leader on the team building the foundational data infrastructure that will unlock this potential. You will take a leading role in architecting and scaling the data pipelines and models that underpin our Data business, including our Audiences, Measurement, and FAST products. This is a critical, hands-on role that combines deep technical expertise with strategic thinking and technical mentorship. You will be instrumental in transforming our raw data into productized, outcome-driven assets that serve the world's largest brands and platforms.

Requirements

• 5+ years of experience in analytics engineering, data engineering, or a related field, with a proven track record of building scalable data solutions.
• Hands-on experience working with advertising technology data structures or platforms (e.g., ad servers, DSPs, SSPs, CDPs, clean rooms, or identity graphs), and understanding how data flows support activation and measurement workflows.
• Demonstrates technical leadership, helping guide a team’s architectural decisions, data modeling standards, and approach to complex engineering problems.
• Deep technical expertise in the modern data stack, including data warehousing (Snowflake, BigQuery, or Redshift), data transformation (DBT), and orchestration (Airflow).
• Proficient in authoring and optimizing complex SQL, with a strong understanding of OLAP/OLTP database principles and query performance tuning.
• Experience architecting data models for advertising technology, including concepts like impressions, conversions, audience segmentation, and measurement/attribution.
• Proven ability to partner with cross-functional stakeholders to translate complex business requirements into technical solutions.
• Excellent communication skills, with the ability to articulate complex technical concepts to both engineering teams and non-technical business leaders.
• Proficiency in at least one imperative programming language (e.g., Python) and familiarity with software engineering best practices (CI/CD, automated testing).
• A strategic mindset and the ability to operate effectively in a dynamic, fast-paced environment.

Nice To Haves

• Experience with data monetization strategies and building Data-as-a-Service (DaaS) products.
• Experience in data architecture for scaled data products or revenue-linked systems preferred.
• Familiarity with data clean room technologies and other privacy-enhancing data collaboration methods.
• Direct experience working with major ad platforms, agencies, or measurement partners like Amazon, LiveRamp, or The Trade Desk.
• Knowledge of data privacy regulations (e.g., GDPR, CCPA) and experience building systems with a privacy-first approach.

Responsibilities

• Technical Leadership and Mentorship: Act as a technical leader and mentor for other engineers on the team. Drive technical excellence, lead by example on engineering best practices, and contribute to raising the bar for the entire team.
• Architect and Design: Play a pivotal role in designing and architecting the data infrastructure that powers our data monetization products. Make key decisions on data modeling, pipeline construction, and tooling to ensure scalability and reliability.
• Build and Optimize: Design, develop, and optimize robust, scalable data pipelines using DBT, Airflow, and cloud data platforms (e.g., Snowflake) to handle terabytes of transactional and behavioral data. Write SQL that is not just correct, but highly performant at scale.
• Enable Ad Tech Integrations: Build and maintain data models and pipelines that power activation, targeting, and measurement use cases across major advertising technology platforms, leveraging Fetch’s first-party purchase data to improve campaign precision and performance.
• Collaborate and Influence: Collaborate closely with leaders and peers in Product, Engineering, and Go-to-Market, as well as with potential clients, to translate the data product strategy into a technical reality. Influence technical decisions to ensure alignment with revenue goals and commercial sequencing.
• Data Product Mindset: Design and build data assets as reusable, productized components that drive monetization, ensuring each model serves a clear customer or commercial outcome.
• Scale for Growth: Architect and build systems designed for massive scale, supporting initiatives like our productized clean room integrations and automated custom audience creation.
• Champion Data Quality: Establish and enforce best practices for data modeling, data quality, governance, and documentation to ensure our data products are trusted and reliable measurement currency in the industry.
• Lead Performance Optimization: Take ownership of performance tuning and cost management of our data stack, ensuring our data models and queries are efficient and cost-effective.
• Enable the Business: Empower stakeholders with the analytical assets needed to drive deeper insights into ad engagement, campaign effectiveness, and monetization strategies, directly contributing to our ambitious revenue goals.

Benefits

• At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire.
• Discover our benefits and how our employees live rewarded at https://fetch.com/careers.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed