Senior Analytics Engineer

Company description Profitero+ is the leading digital commerce company, trusted by more than 4,000 brands worldwide. We help brands break down silos and turn data into decisive action through intelligence-driven, end-to-end solutions that unify media, content, operations and strategy. Powered by advanced AI, robust digital shelf analytics across 1,400+ retailers in 70 countries and unmatched expertise from digital commerce specialists in 15 global hubs, our integrated solutions help brands accelerate profitable growth. Learn more at profitero.com Overview 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 Qualifications 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. Additional information The Power of One starts with our people! To do powerful things, we offer powerful resources. Our best-in-class wellness and benefits offerings include: Paid Family Care for parents and caregivers for 12 weeks or more Monetary assistance and support for Adoption, Surrogacy and Fertility Monetary assistance and support for pet adoption Employee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance Tuition Assistance Paid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more Matching Gifts programs Flexible working arrangements ‘Work Your World’ Program encouraging employees to work from anywhere Publicis Groupe has an office for up to 6 weeks a year (based upon eligibility) Business Resource Groups that support multiple affinities and alliances The benefits offerings listed are available to eligible U.S. Based employees, are reviewed on an annual basis, and are governed by the terms of the applicable plan documents. Profitero+ is an Equal Opportunity Employer. Our employment decisions are made without regard to actual or perceived race, color, ethnicity, religion, creed, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, childbirth and related medical conditions, national origin, ancestry, citizenship status, age, disability, medical condition as defined by applicable state law, genetic information, marital status, military service and veteran status, or any other characteristic protected by applicable federal, state or local laws and ordinances. If you require accommodation or assistance with the application or onboarding process specifically, please contact [email protected]. All of your information will be kept confidential according to EEO guidelines. Compensation Range: USD $88,540.00 - USD $121,100.00/Annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 8/29/2026.

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.

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