{"id":2301172,"url":"https://alion.io/job/mercury-insurance-data-analytics-engineer-ii","title":"Data Analytics Engineer II","company":{"id":8014,"name":"Mercury Insurance","domain":"mercuryinsurance.com","url":"https://alion.io/company/mercury-insurance","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":94458,"max":179048,"currency":"USD","period":"year","gross":null,"usd_annual":179048},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"BigQuery","optional":false},{"name":"dbt","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Django","optional":true},{"name":"Flask","optional":true},{"name":"Rest API","optional":true}],"status":"live","first_seen_at":"2026-10-11T21:06:48Z","employer_posted_date":"2026-10-11","last_verified_at":"2026-10-13T12:16:23Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Overview\nPosition Summary:\nWe’re looking for an Analytics Engineer II to build our next-generation enterprise metrics store and enable insights across underwriting, sales, product, claim and experience. This role blends analytics engineering and prompt engineering, supporting our journey toward a fully governed, AI-ready data ecosystem.As an Analytics Engineer, you will sit at the intersection of:\ndata modeling (dbt, semantic layer)\nbusiness metrics (insurance domain: quotes, binds, premium, agency performance)\nanalytics engineering (root cause analysis, metric relationships, metric store)This is a hands-on role where you will design, build, and scale core metrics and analytical workflows, working closely with product, business, and engineering stakeholders. The team is evolving toward exposing metric infrastructure as internal services, so you’ll have the opportunity to shape that API layer as it matures.\nGeo-Salary Information\nAn in-person interview may be required during the hiring process\nState specific pay scales for this role are as follows:\n$94,458 to $179,048 (CA, NJ, NY, WA, HI, AK, MD, CT, RI, MA)\n$85,871 to $162,771 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME)\n$77,283 to $146,494 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV)\nThe expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location.\nResponsibilities\nEssential Job Functions:\nBuild and scale the metric layer\nDevelop and maintain dbt models\nContribute to semantic layer definitions (metrics, dimensions, relationships)Ensure consistency and correctness of: key business metrics o metric hierarchies (metric pyramid)\nImplement analytical logic (root cause analysis & metric insights)\nBuild root cause analysis workflows:Implement baseline comparisons , companion metric analysis\nTranslate business questions into scalable analytical patterns\nEnable metric consumption across toolsSupport metric usage in different BI or analytical tools\nBuild reusable logic that avoids duplication across tools\nPrepare for future API-based metric serving layer\nPartner with business and product stakeholders\nWork closely with sales, product, underwriting, claims, experience and other business teams, Translate ambiguous questions into:\nStructured metrics\nActionable insights\nImprove data quality and governance\nDefine and enforce:\nMetric definitions\nDimension standards\nData contracts\nDebug issues across:\nUpstream pipelines\nSemantic layer\nAnalytical outputs\nQualifications\nEducation:\nBachelor's Degree in Computer science, Statistics or similar \n3-5 years of analytics engineering or similar analytical role experience with dbt or similar transformation frameworks proficiency: models, tests, incremental materialization, Jinja macros\nAdvanced SQL on a columnar warehouse (Redshift, Snowflake, or BigQuery)\nPython for data transformation and analysis (pandas, basic scripting)\nComfort working with YAML-based configuration and version-controlled analytics workflows\nClear written and verbal communication-able to explain metric definitions and data lineage to non-technical stakeholders\n Nice to have P&C insurance domain experienceExperience with:Cohort analysisFunnel metricsPerformance analysisFamiliarity with MetricFlow specifically and the dbt Semantic LayerExposure to Retool or similar low-code tools for operational write-back workflowsFastAPI or similar Python API frameworks (Flask, Django REST) for serving data products as services\nAbout the Company\nWhy choose a career at Mercury?\nAt Mercury, we have been guided by our purpose to help people reduce risk and overcome unexpected events for more than 60 years. We are one team with a common goal to help others. Everyone needs insurance and we can’t imagine a world without it.\nOur team will encourage you to grow, make time to have fun, and work together to make great things happen. We embrace the strengths and values of each team member. We believe in having diverse perspectives where everyone is included, to serve customers from all walks of life.\nWe care about our people, and we mean it. We reward our talented professionals with a competitive salary, bonus potential, and a variety of benefits to help our team members reach their health, retirement, and professional goals.\nLearn more about us here: https://www.mercuryinsurance.com/about/careers\nPerks and Benefits\nWe offer many great benefits, including:\nCompetitive compensation\nFlexibility to work from anywhere in the United States for most positions\nPaid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours)\nIncentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus)\nMedical, dental, vision, life, and pet insurance\n401 (k) retirement savings plan with company match\nEngaging work environment\nPromotional opportunities\nEducation assistance\nProfessional and personal development opportunities\nCompany recognition program\nHealth and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more\nMercury Insurance is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by federal, state, or local law.\nPay Range\nUSD $94,458.00 - USD $179,048.00 /Yr.","description_format":"text","description_chars":5544,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Education assistance","Retirement plans"],"hiring_locations":[{"name":"United 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