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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Analytics Engineer - **Company:** Publicis Groupe - **Location:** Lehi, UT, United States - **Experience:** Expert - **Salary:** $88,540.0 - **Contract:** Temporary contract - **Skills:** Airflow, Data Analysis, Business Logic, Automation of Tests, Business Intelligence Development, BigQuery, Information Systems, Directed Acyclic Graph (Directed Graphs), Information Engineering, Data Governance, Document-Oriented Databases, Raw Data, Standard Sql, SQL Databases, Datadog, Information Technology, Data Analytics, Google Shopping, Looker Analytics, Data Pipelines - **Published:** July 10, 2026 - **Apply:** https://www.juju.com/job/00000000gfd9y9 ## About the Role + 5+ years of professional experience in data engineering, analytics engineering, or a similar role; prior experience working alongside the CPG, retail, and/or marketing industries preferred. + Bachelor's degree in computer science, data analytics, information systems, or a related field preferred; experience may be substituted. + Expert-level dbt skills including experience building and maintaining production dbt projects at scale including tests, documentation, and incremental models. + Strong SQL and data modeling skills, particularly in BigQuery or another columnar cloud data warehouse. + Experience working across the full data pipeline from raw ingestion to BI-ready models. + Familiarity with ecommerce, CPG, digital shelf, or retail media network data sources and analytics preferred. + Experience with Airflow or Dagster for pipeline orchestration and Python for data pipeline tasks preferred. + Familiarity with Looker or LookML preferred. + Experience and familiarity with data quality frameworks, automated testing, or observability tooling preferred. + Comfort operating with a high level of ownership, autonomy, and accountability. + A natural sense of urgency with an ability to work quickly, efficiently, and accurately within tight deadlines and constantly-evolving project parameters, scope, and goals. + Flexible and adaptable with an ability to work successfully across multiple concurrent projects and competing priorities. + Highly collaborative but independently capable. + Exceptionally organized with a fanatical attention to detail. + Strong written and verbal communication skills, both with technical and non-technical audiences. ## Description Profitero's Data Engineering team is looking for a **Senior Analytics Engineer** to own the transformation layer between our data ingestion pipelines and our business intelligence platform. This is a high-impact, high-ownership role at the center of our data stack - you will define how raw data becomes trusted, business-ready models that power decisions across the organization. PLEASE NOTE: This is a hybrid role based out of our offices in Lehi, Utah and will require onsite engagement an average of 1-2 days/week. All candidates should be local to or commutable to Lehi (including surrounding locations like Salt Lake City or other south Utah counties) and willing to commit to a hybrid schedule. Highly qualified candidates from other US-based locations who are willing to work a Mountain Time schedule may also be considered and are encouraged to apply. ALSO NOTE: We are not able to provide sponsorship support for this role now or in the future. No third-party staffing agencies, please. Responsibilities + Own the Transformation Layer + Design, build, and maintain dbt models that transform raw source data into clean, well-documented, analytics-ready datasets + Define and enforce dbt modeling standards, naming conventions, and testing practices across the team + Serve as the primary owner of the transformation layer, creating clear handoffs with upstream ingestion engineers and downstream BI developers + Proactively identify gaps in data coverage and work with sourcing teams to resolve them + Accelerate Pipeline Delivery + Reduce transformation backlogs by building scalable, reusable model patterns that others can extend + Partner with Airflow/Dagster pipeline owners to ensure transformation DAGs are reliable, well-monitored, and efficient in BigQuery + Identify and resolve performance bottlenecks in SQL transformations and BigQuery query patterns + Bridge Engineering and Analytics + Collaborate with BI developers and the Director of Business Intelligence to ensure Looker data sources are well-modeled and maintainable + Translate business requirements from stakeholders into reliable data models without requiring BI developers to work around messy upstream data + Help evolve manual QA processes toward automated dbt testing and data quality monitoring + Mentor and Set Standards + Mentor junior and mid-level team members on analytics engineering best practices + Document data models, lineage, and transformation logic so the team can move faster and onboard new members with confidence + Contribute to SQL and business logic standards in collaboration with the Director of Data Engineering ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [The OpenTelemetry mistakes I keep seeing (and how to stop making them)](https://www.wearedevelopers.com/videos/100158-the-opentelemetry-mistakes-i-keep-seeing-and-how-to-stop-making-them) - [Making Data Warehouses fast. 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