Data Analytics Engineer

Role Description

We're looking for a Senior Analytics Engineer to join our Data Operations team to own the reliability, release, and customer-facing correctness of Antenna's core data products. This role will sit at the intersection of Commercial, Data Science, and Engineering, and makes judgment calls that materially affect customer trust and business decisions.

In this role, you will report directly to the VP of Data Operations.

What You’ll Do

• Partner with our Commercial team to understand how our customers use Antenna data to inform critical business decisions – and design and build data solutions that allow them to do that with zero friction.
• Manage the end-to-end data product release, prioritizing tasks and project-managing cross-functional teams to ensure accurate, reliable, and on-time delivery of data to all internal and external stakeholders.
• Develop and deploy strategic product improvements that maximize both data quality and business impact.
• Build and optimize systems to proactively monitor data quality at each stage of the pipeline. Perform root cause analyses and find scalable solutions with minimal oversight.
• Investigate anomalous data to make a judgment call on whether trends represent data quality errors or real-world events.
• Act as the first responder for data issues and inquiries. Educate commercial stakeholders about data definitions and nuances.
• Manage updates to QA tests and dashboards to streamline ongoing QA checks.
• Investigate data restatements and data science models. Coordinate data fixes in partnership with Engineering and Data Science teams (internally) and data vendors (externally).
• Perform data quality investigations to understand why Antenna data does not align to customer’s first party data. Present findings to customers directly.
• Run new coverage feasibility, and propose solutions to update methodology and pipeline capabilities.
• Coordinate monthly data releases in Looker, and weekly data releases via ad hoc reports.

Qualifications

• Strategic thinker with 7+ years of hands-on experience in data-focused roles.
• Expert in SQL, Excel, DBT and business intelligence tools (e.g. Looker, Redash), comfortable navigating complex ETL systems and messy data.
• Proven ability to organize, analyze and vet large volumes of data with great attention to detail.
• Strong communication and stakeholder management skills; able to translate technical concepts and align Data Ops initiatives with customer-centric objectives.
• Passionate about solving customer problems.
• Self-starter with the ability to carry multiple initiatives, prioritize time and resources, and meet deadlines in a fast-moving environment.
• Bonus: Experience using automation tools and AI-driven solutions to streamline data workflows and elevate data product reliability.