{"id":1126780,"url":"https://alion.io/job/protective-life-lead-data-engineer","title":"Lead Data Engineer","company":{"id":4251,"name":"Protective Life","domain":"protective.com","url":"https://alion.io/company/protective","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Birmingham, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":109500,"max":167833,"currency":"USD","period":"year","gross":null,"usd_annual":167833},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Git","optional":false},{"name":"Least Privilege","optional":false},{"name":"Python","optional":false},{"name":"Scrum","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Great Expectations","optional":true},{"name":"MLFlow","optional":true}],"status":"live","first_seen_at":"2026-09-15T20:59:57Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-10-17T05:28:37Z","board_verified":true,"closed_at":null,"days_open":31,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":31},"description":"Protective is looking for a Lead Data Engineer to set the technical direction for a delivery pod building data products on Voyager, our Databricks lakehouse on Azure. You will lead the design of data products through the full medallion architecture - Bronze ingestion, Silver conformance, and Gold consumption - and be accountable for whether those products hold up for the consumers who depend on them.\nThis is a hands-on technical leadership role, not a people-management or project-management role. You will still write and review production code daily. What you own is how the pod’s data products are designed, modeled, contracted, and tested, and the standard the pod holds itself to. The Product Owner owns the backlog and the Scrum Master owns the sprint; you own the engineering.\nOn Voyager, the medallion layers are named Raw, Prep, and Prod. They map directly to Bronze, Silver, and Gold and are used interchangeably in this description.\nKey Responsibilities\nDesign and modeling\nLead the design of data products end to end: what gets ingested, how it is cleansed and conformed, how it is modeled, and what the Gold layer looks like to the people querying it.\nOwn dimensional design - grain, natural and surrogate keys, Type 2 history, facts, bridges, and conformed dimensions shared across the pod’s products.\nSet the pod’s position on where logic belongs: what is cleaned in Silver, what is business logic in Gold, and what is a consumer’s own concern.\nKeep models as simple as the questions require, and push back on designs that will not hold.\nPartner with ML engineering where the pod’s Gold layer is the training or feature source for a model, so those datasets are contracted, versioned, and reproducible like any other consumer-facing product.\nData contracts and consumer compatibility\nOwn the pod’s ODCS data contracts as real interfaces: named owners, named consumers, enforceable quality rules, freshness and update expectations, and an explicit breaking-change policy.\nMake the compatibility call on every proposed contract change, and drive consumer notification when a change is genuinely breaking.\nRepresent the pod’s contracts in cross-domain conversations, where one pod’s Gold layer is another team’s dependency.\nStandards, quality, and operations\nSet and hold the pod’s engineering standards for Python, SQL, dbt, testing, model structure, naming, and repository conventions - consistent with the platform’s paved paths and Azure DevOps CI gates rather than in competition with them.\nLead code review. Be the reviewer who catches the modeling mistake, the missing test, and the change that will break a consumer, and who explains why so the pod learns it.\nEnsure quality rules are enforced in tests and asset checks rather than asserted in documentation, and that pipeline health is observable without someone going to look - freshness, volume, latency, and cost instrumented, and alerting set against the SLAs and SLOs the pod’s contracts commit to.\nOwn the pod’s operational posture for its own pipelines: failure diagnosis, data-issue triage, backfills, cost and performance tuning, on-call coverage and escalation, root-cause analysis, and runbooks someone other than the author can execute.\nKeep the pod’s delivery inside the control expectations of a regulated carrier: change management through pull request and pipeline, segregation of duties between authoring and deploying, least-privilege access, and audit evidence that falls out of CI/CD rather than being assembled for an auditor.\nDevelop reusable frameworks, templates, and patterns that raise the pod’s consistency and delivery speed.\nDelivery leadership\nPartner with the Product Owner and Scrum Master on decomposition and refinement: turn use cases and features into estimable, grounded stories with testable acceptance criteria and an identified target layer and repository.\nHold the Definition of Ready before the pod commits and the Definition of Done before the pod calls something finished - merged and approved code, passing CI and coverage gates, and evidence that the outcome is real.\nIdentify unknowns that need a spike rather than an estimate, and say so during planning rather than mid-sprint.\nMentorship and collaboration\nGrow the engineers on the pod through design review, pairing, and code review rather than by taking the hard work yourself.\nBring new engineers up to productive speed on the platform’s conventions and tooling, and reduce single points of knowledge - no data product that only one person understands.\nWork with the platform team on capability gaps: when the pod needs something the platform does not yet offer, raise it as a demand signal rather than building a private workaround.\nPartner with the DataOps/MLOps Lead on the shared CI/CD, orchestration, and observability standards - adopt and strengthen the paved path rather than forking it, and be the pod’s voice on what it is still missing.\nWork with data architecture and governance on solution shape, Unity Catalog placement, and access requirements.\nQualifications\nRequired Qualifications\nBachelor’s degree in Computer Science, Information Systems, Engineering, or a related field; equivalent practical experience considered.\n6+ years building and operating production data pipelines and consumer-facing data models, from source ingestion through to published data products.\nStrong hands-on Python and SQL, with the credibility to make design calls and the willingness to still write and review code.\nHands-on experience with Databricks or a comparable Spark-based lakehouse, including Delta Lake, MERGE, incremental processing, and performance tuning.\nDeep dimensional modeling experience - grain, keys, slowly changing dimensions, facts and dimensions, conformed dimensions.\nDemonstrated technical leadership: setting standards, leading design, and raising other engineers’ work, whether or not the role carried a lead title.\nExperience owning data that other teams depend on, including handling breaking changes and production data incidents.\nExperience with orchestration (Dagster, Databricks Workflows, Airflow, or similar), Git-based collaborative development, code review, and CI/CD - Azure DevOps or comparable.\nExperience setting observability and SLA/SLO expectations for data other teams depend on, and running the incident and communication path when they are missed.\nAbility to explain trade-offs clearly to engineers, product owners, and business stakeholders, and to say no to a design that will not hold.\nPreferred Qualifications\nDatabricks certification (Data Engineer Professional or equivalent demonstrated depth).\nUnity Catalog at multi-team scale: catalogs, schemas, external locations, permissions, and lineage.\ndbt at scale on Databricks, and Python-based modeling frameworks over Delta Lake.\nDagster and Dagster Cloud, including assets, asset checks, and branch deployments.\nPractical experience with data contracts, ODCS, or data-mesh style data product ownership.\nExperience with a declarative Python ingestion framework such as dlt (dltHub) or comparable.\nData quality and observability tooling such as Great Expectations, Monte Carlo, or similar.\nFamiliarity with MLOps practice - MLflow, model registries, and model serving - sufficient to design data products that ML systems can depend on.\nAzure and Azure DevOps.\nFinancial services, insurance, or another regulated industry, including data access, lineage, and audit expectations.\nExperience introducing AI-assisted development into a team’s normal workflow in a disciplined way.","description_format":"text","description_chars":7548,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Life Insurance & Annuities"],"lifecycle":[{"event":"open","at":"2026-09-22T22:05:16Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 3","filings_12m":3,"filings_prev_12m":1,"green_card_filings_12m":0,"median_offered_wage_usd":142500,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":1}],"liveness":{"score":56,"band":"ok","label":"Likely open","p_open":1,"p_active":0.741,"p_room":0.75,"age_days":31,"expected_fill_days":41,"reasons":["conf:0","win:late"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":167833,"is_top_pay":false},"html_url":"https://alion.io/job/protective-life-lead-data-engineer","json_url":"https://alion.io/job/protective-life-lead-data-engineer.json","meta":{"generated_at":"2026-10-17T06:24:33Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":8652,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4251},"rest":"https://alion.io/mcp/rest/get_company?id=4251"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fprotective-life-lead-data-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fprotective-life-lead-data-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fprotective-life-lead-data-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/protective-life-lead-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fprotective-life-lead-data-engineer"}]}