{"id":1804174,"url":"https://alion.io/job/masco-data-engineering-leader","title":"Data Engineering Leader","company":{"id":2746766,"name":"Masco","domain":"masco.com","url":"https://alion.io/company/masco-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Livonia, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":103700,"max":163020,"currency":"USD","period":"year","gross":null,"usd_annual":163020},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Incident Management","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"MS SQL","optional":false},{"name":"Python","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Kanban","optional":true},{"name":"MLFlow","optional":true}],"status":"live","first_seen_at":"2026-10-01T00:00:00Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-05T01:47:58Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Role Summary\nThe Data Engineering Leader owns the delivery, quality, and operational health of Masco's enterprise data engineering capability. Reporting to the Enterprise Data Architect, this role leads a team of Data Engineers building andoperatingthe ingestion, transformation, and Lakehouse solutions that power enterprise POS and adjacent commercial data. This is a hands-on technical leader who codes alongside the team, holds engineers accountable to project plans and SLAs, and provides architectural support to the Enterprise Data Architect on ingestion patterns, pipeline design, and platform decisions. The Data Engineering Leader partners closely with the BI Delivery Leader to ensure enterprise data structures and models are in place foraccurate,timelyanalyticsdelivery.\nWhat You'll Own\nEngineering Team Leadership & Delivery Accountability\nLead, coach, and manage a team of Data Engineers, including performance guidance and prioritization.\n\nHold the team accountabletoproject plans, sprint commitments, and quality expectations.\n\nCoordinate onshore and offshore engineering capacity, serving as the technical lead for offshore engineering resources and the bridge back to onshore leads.\n\nSequence sprint delivery against the priority roadmap and requirements set by the Enterprise Data Architect, Technical Product Owner, and Business Data Analyst.\n\nIngestion, Pipeline & Data Platform Build\nOwn the build and operation of ingestion pipelines across retailer, HQ, and BU data sources on the Databricks and Azure data stack.\n\nContribute directly as a senior engineer on critical-path pipelines, Lakehouse design, and modeling work.\n\nPartner with the Architect to build the ingestion side of the attribution crosswalk and master data foundations to the documented spec.\n\nEnforce data-validation gates for completeness, outliers, and consistency before data reaches enrichment.\n\nIncident Management, Release Management & Operational SLAs\nOwn intake, triage, and resolution of pipeline incidents and data issues raised by BU and HQ consumers.\n\nOwn release management for engineering enhancements, requests, and projects, including development operations, sprint execution, deadlines, and delivery of the business value defined by the Business Data Analyst and Technical Product Owner.\n\nEstablish and adhere to SLAs for incident response, resolution, and communication back to consumers.\n\nOwn monitoring, alerting, and operational health of pipelines, credentials, and source integrations.\n\nEscalate issues that touch the enterprise model, masters, or attribution to the Enterprise Data Architect.\n\nCloud Cost & Consumption Management\nMonitor cloud storage, compute, and consumption of enterprise data platforms, and track related costs.\n\nContributeto budgeting for cloud, data services, and engineering tools, informed by consumption trends and workload forecasts.\n\nRecommend cost optimization actions such as right-sizing, workload tuning, and storage tiering as part of ongoing platform operations.\n\nArchitecture Support & Analytics Delivery Enablement\nServe as a delivery-side extension of the Enterprise Data Architect, advising on ingestion patterns, Lakehouse design, and platform decisions.\n\nEnforce enterprise standards for data engineering, integration, and data quality in all work delivered by the team.\n\nWork closely with the BI Delivery Leader to ensure enterprise data structures, models, and metric definitions are in place foraccurateandtimelyanalytics delivery.\n\nStay connected to BU data engineering counterparts for collaboration, cross-learning, and consistent enterprise practice.\n\nDocumentation & Knowledge Management\nEstablish andenforce howengineeringdocumentation worksacross the team, in partnership with the Enterprise Data Architect.\n\nOwn documentation standards for pipelines, ingestion patterns, operational runbooks, credentials management, incident response, and release management.\n\nEnsure engineers document changes to metrics, pipelines, and data flows as part of the definition of done.\n\nRequired Qualifications\nEducation & Experience\nBachelor's orMaster's degree in Computer Science, Engineering, Data Analytics, or a related field; equivalent professional experience considered.\n\nProven experience ina dataengineering leadership role, including managing engineers and delivery accountability.\n\nSubstantial hands-on experience designing and building scalable data engineering solutions on a major cloud platform, with emphasis on the Azure ecosystem.\n\nExperience running incident management and SLA-driven support for data pipelines.\n\nExperience coordinating onshore and offshore engineering delivery.\n\nTechnical Skills\nAdvanced hands-onexpertisewithDatabricks and the Azure data stack (Data Factory, Data Lake, Synapse, Analysis Services).\n\nDeep working knowledge of the medallion architecture (bronze / silver / gold) for structuring Lakehouse solutions.\n\nUnderstanding ofand experience withMicrosoft Fabric, including how it fits alongside Databricks in a modern enterprise data platform.\n\nAdvanced SQL / T-SQL and strong ETL/ELT design and build experience.\n\nStrongproficiencyin Python for data engineering.\n\nWorking knowledge of distributed processing and Lakehouse principles.\n\nSolid understanding of CI/CD, DevOps, and automation for data workflows.\n\nStrong understanding of Kimball dimensional modeling and enterprise semantic layers.\n\nUnderstanding ofdata governance, security, and compliance as they apply to enterprise data engineering.\n\nSkills & Competencies\nPlayer-coach mindset. Leads the team and still contributes directlyoncritical-path engineering work.\n\nDelivery-driven. Owns commitments, SLAs, and follow-through.\n\nWillingness to explore and understand new and modern data tools to add value to the enterprise POS and POS-related engineering space.\n\nCollaborative with BU data engineering counterparts for cross-learning and consistent practice.\n\nStrong communicator who can translate engineering realities for business and leadership, and architectural direction for engineers.\n\nDetail-oriented, self-directed, and a continuous learner on modern data engineering practices.\n\nAbility to leadteamand manage career development forsmallnumber of direct reports.\n\nPreferred Qualifications\nExperience in retail, consumer goods, or manufacturing analytics environments where POS, sell-in, inventory, and third-party retail data are core.\n\nExperience with Databricks Unity Catalog, data lineage, and observability tools.\n\nExperience withPowerBI.\n\nFamiliarity with ML/AI integration (MLflow, Azure ML) andDataOps/MLOpspractices.\n\nExperience with RESTful API development for data acquisition.\n\nFamiliarity with modernDataOps, Agile, or Kanban delivery practices.\n\nCompany: Masco\nFull timeHiring Range: $103,700.00 - $163,020.00 USDActual compensation may vary based on various factors including experience, education, geographic location, and/or skills.Masco Corporation (the “Company”) is an equal opportunity employer and we strive to employ the most qualified individuals for every position. The Company makes employment decisions only based on merit. It is the Company’s policy to prohibit discrimination in any employment opportunity (including but not limited to recruitment, employment, promotion, salary increases, benefits, termination and all other terms and conditions of employment) based on race, color, sex, sexual orientation, gender, gender identity, gender expression, genetic information, pregnancy, religious creed, national origin, ancestry, age, physical/mental disability, medical condition, marital/domestic partner status, military and veteran status, height, weight or any other such characteristic protected by federal, state or local law. The Company is committed to complying with all applicable laws providing equal employment opportunities. This commitment applies to all people involved in the operations of the Company regardless of where the employee is located and prohibits unlawful discrimination by any employee of the Company.\nMasco Corporationis an E-Verify employer. E-Verify is an Internet based system operated by the Department of Homeland Security (DHS) in partnership with the Social Security Administration (SSA) that allows participating employers to electronically verify the employment eligibility of their newly hired employees in the United States. Please click on the following links for more information.\nE-Verify Participation Poster:English & Spanish\nE-verify Right to Work Poster:English, Spanish","description_format":"text","description_chars":8511,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-03T18:58:24Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 1","filings_12m":1,"filings_prev_12m":1,"green_card_filings_12m":0,"median_offered_wage_usd":127500,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":0}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":3,"expected_fill_days":20,"reasons":["conf:0","win:early"],"computed_at":"2026-10-04T05:45:00Z"},"pay":{"stated_usd_annual":163020,"is_top_pay":false},"html_url":"https://alion.io/job/masco-data-engineering-leader","json_url":"https://alion.io/job/masco-data-engineering-leader.json","meta":{"generated_at":"2026-10-05T03:00:22Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4108,"day_limit":5000,"remaining_today":892,"minute_limit":60,"resets_at":"2026-10-06T00:00:00Z"}}}