{"schemaVersion":"jobsearcher.job.v1","id":"3cc45c475367f9810fc01624","url":"https://jobsearcher.com/jobs/3cc45c475367f9810fc01624","canonicalUrl":"https://jobsearcher.com/jobs/3cc45c475367f9810fc01624","title":"Senior Data Analytics Engineer","description":"We’re building a modern analytics practice that goes beyond dashboards. Starting with revenue-focused sales analytics using ERP + non-ERP sources (customer POS, CRM, industry data, spreadsheets, and other structured/unstructured sources), this role will establish reusable analytics foundations (certified datasets, standardized metrics, semantic layer) that reduce ad-hoc reporting and democratize insight generation — with scope expanding over the first year to support Supply Chain, Manufacturing, Quality, and broader Financials analytics as the foundation matures.\n\nThis is an in-office position in Phoenix, Arizona.\n\nESSENTIAL FUNCTIONS & RESPONSIBILITIES\n\nTo perform this job successfully, an individual must be able to perform each essential function satisfactorily:\n\nA) Sales & Finance revenue analytics and decision enablement (first 6 months priority)\n\nPartner with Sales and Finance to build a differentiated sales analytics product that improves decision-making on revenue drivers (e.g., pricing/discounting, mix, customer/segment performance, channel).\nCreate executive-ready insight narratives and repeatable analytic “decision frameworks” (driver trees, leading indicators, KPI hierarchies).\nIntegrate and reconcile new sources beyond ERP (e.g., customer POS feeds, CRM, external/industry signals, customer master enrichment, spreadsheets) into governed analytical datasets.\n\nB) Expansion domains: Supply Chain, Manufacturing & Quality (year-one roadmap)\n\nAs the Sales & Finance analytics foundation matures, extend the same certified-dataset and semantic-layer approach to additional functional domains, sequenced and prioritized jointly with IT and business leadership.\nSupply Chain: inventory, fulfillment, and demand-planning analytics sourced from JDE and related systems.\nManufacturing: production throughput, downtime, and cost/efficiency analytics.\nQuality: defect and scrap trends, supplier quality performance, and corrective-action tracking, drawing primarily on SQL Server-based operational data alongside other source systems.\nData across these domains lives in multiple systems, predominantly SQL-based databases — consistent modeling and reconciliation practices across sources will be essential.\nThis work begins after Sales & Finance foundations are established; exact scope and sequencing will be set collaboratively based on business priority, not assumed to run in parallel from day one.\n\nC) Analytics engineering: data products, semantic layer, and standardized metrics\n\nDesign and own curated analytics datasets and reusable dimensional models that become a “single source of truth” across the functional domains in scope.\nEstablish and enforce consistent KPI definitions via a metrics/semantic layer approach (define metrics once, reuse everywhere).\nImplement testing, documentation, and data-quality practices so stakeholders trust and adopt the analytics outputs.\n\nD) Self-service enablement & analytics democratization\n\nReduce ad-hoc reporting by delivering certified datasets, reusable templates, and clear consumption patterns that allow business users to self-serve safely.\nEstablish training/enablement (office hours, best-practice templates, “how to use” documentation) and analytics community rituals.\n\nE) Contribute to the Analytics Community of Practice\n\nContribute to the design of an Analytics COE operating model — one focused on standards, adoption, and scalable enablement rather than report-factory or help-desk patterns.\nPartner with IT leadership to help shape and execute a 12 to 18-month roadmap for analytics capabilities across the domains in scope (platform patterns, data products, priority areas, adoption metrics).\n\nF) Modern tooling & innovation (governed)\n\nImplement analytics CI/CD patterns (e.g., version control, release discipline, peer review) to scale reliably.\nApply AI-assisted techniques (e.g., anomaly detection, driver analysis, AI-assisted query or code generation) to accelerate analytics delivery where they improve time-to-insight and adoption.\nWork within an AI-enabled analytics environment, including enterprise-grade AI tooling already in use across EMG IT, governed under our Group Responsible AI Policy (accountability, fairness, reliability, transparency).\n\nQUALIFICATIONS\n\nThe requirements listed below are representative of the knowledge, skills, and/or abilities required for this position.\n\nEducation and/or Experience:\n\n8–10+ years in analytics/BI/data roles with evidence of business impact and cross-functional partnership.\nPrior experience directly managing or supervising technical staff (e.g., a data engineer or analyst) is required — this role has a formal direct report.\nExpert SQL + strong data modeling (facts/dimensions; performance-aware).\nProven ability to create reusable analytics assets (certified datasets, metric definitions, semantic consistency) that generalize across business domains, not just one function.\nStrong business acumen and ability to proactively propose analyses (not just take requirements).\nExposure to supply chain, manufacturing, or quality analytics is a plus but not required — Sales & Finance domain depth is the priority for this hire; other domains will be learned on the job as scope expands.\nWorking knowledge of Python for data automation, scripting, and analysis is a plus. Deep statistical or machine learning expertise is not required for this role.\nComfort applying AI-assisted techniques (e.g., anomaly detection, driver analysis, AI-assisted query/code generation) to accelerate analytics work is a plus — willingness to learn is sufficient; deep AI/ML expertise is not required.\n\nWhat success looks like (6 months)\n\nA Sales & Finance revenue analytics capability that integrates non-ERP signals and is actively used by Sales leadership for pricing/revenue decisions.\nMeasurable reduction in ad-hoc reporting through certified datasets, templates, and defined intake/triage patterns.\nA well-managed, productive direct report with clear goals and growth plan in place.\nActive contribution to a functioning Analytics Community of Practice with an agreed 12–18-month roadmap and adoption goals.\nA scoped, prioritized plan (not full delivery) for Supply Chain, Manufacturing, and Quality analytics expansion.\n\nComputer Skills\n\nProficiency in MS Office.\nStrong relational database knowledge is a must, including hands-on experience with MS SQL Server and dimensional/star-schema modeling — the majority of source data across functional domains resides in SQL-based systems.\nExperience with Power BI and Analysis Services development (measures, semantic models, DAX) strongly preferred.\nExperience with Microsoft Fabric (Lakehouse, Data Pipelines, OneLake) and/or Azure Data Factory for data ingestion and transformation strongly preferred. Microsoft Certified: Fabric Analytics Engineer Associate or equivalent is a plus. Candidates without direct Fabric experience but with strong dimensional modeling and cloud data platform fundamentals (e.g., Snowflake, Databricks) are encouraged to apply — Fabric-specific tooling can be learned on the job.\nKnowledge of SSIS, stored procedures, triggers, and performance tuning.\nFamiliarity with legacy enterprise BI tools (SAP Business Objects, Cognos, QlikView) is a plus for supporting existing reporting during migration, but is not a primary requirement.\nExperience with JD Edwards (JDE) Enterprise One or similar ERP-sourced reporting environments is highly desirable, particularly for future Supply Chain and Manufacturing analytics work.\nStrong knowledge and experience in the Software Development Life Cycle; SCRUM experience and certification is a plus.\n\nLanguage Ability\n\nFor business and safety reasons, ability to write reports and business correspondence in English and effectively present information and respond to questions from groups of managers, clients, customers, technicians, and assemblers in English.\n\nPHYSICAL DEMANDS\n\nPhysical demands described are representative of those that must be met by an employee to successfully perform the essential functions of the job.\n\nWhile performing the functions of this position, the employee is frequently required to sit, stand, walk, stoop and kneel; use hands, reach with hands and arms; communicate clearly and effectively. The employee may also be frequently required to lift up to 10 pounds.\n\nWORK ENVIRONMENT\n\nThe work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this position.\n\nThe noise level in the work and shop environment is moderate to loud.\n\nWhile performing the duties of this position the employee may occasionally be required to work near fumes or airborne particles and toxic or caustic chemicals. The employee may also be required to work near moving mechanical parts.\n\nWe are the ASSA ABLOY Group\nOur people have made us the global leader in access solutions. In return, we open doors for them wherever they go. With nearly 63,000 colleagues in more than 70 different countries, we help billions of people experience a more open world. Our innovations make all sorts of spaces – physical and virtual – safer, more secure, and easier to access.\n\nAs an employer, we value results – not titles, or backgrounds. We empower our people to build their career around their aspirations and our ambitions – supporting them with regular feedback, training, and development opportunities. Our colleagues think broadly about where they can make the most impact, and we encourage them to grow their role locally, regionally, or even internationally.\n\nAs we welcome new people on board, it’s important to us to have diverse, inclusive teams, and we value different perspectives and experiences.","company":"ASSA ABLOY","rawCompany":"assa abloy","city":"Phoenix","state":"AZ","isRemote":false,"isActive":false,"createdAt":"2026-08-31T10:59:35.888Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-2051.01","title":"Business Intelligence Analysts","slug":"business-intelligence-analysts"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Data Analytics Engineer","description":"We’re building a modern analytics practice that goes beyond dashboards. Starting with revenue-focused sales analytics using ERP + non-ERP sources (customer POS, CRM, industry data, spreadsheets, and other structured/unstructured sources), this role will establish reusable analytics foundations (certified datasets, standardized metrics, semantic layer) that reduce ad-hoc reporting and democratize insight generation — with scope expanding over the first year to support Supply Chain, Manufacturing, Quality, and broader Financials analytics as the foundation matures.\n\nThis is an in-office position in Phoenix, Arizona.\n\nESSENTIAL FUNCTIONS & RESPONSIBILITIES\n\nTo perform this job successfully, an individual must be able to perform each essential function satisfactorily:\n\nA) Sales & Finance revenue analytics and decision enablement (first 6 months priority)\n\nPartner with Sales and Finance to build a differentiated sales analytics product that improves decision-making on revenue drivers (e.g., pricing/discounting, mix, customer/segment performance, channel).\nCreate executive-ready insight narratives and repeatable analytic “decision frameworks” (driver trees, leading indicators, KPI hierarchies).\nIntegrate and reconcile new sources beyond ERP (e.g., customer POS feeds, CRM, external/industry signals, customer master enrichment, spreadsheets) into governed analytical datasets.\n\nB) Expansion domains: Supply Chain, Manufacturing & Quality (year-one roadmap)\n\nAs the Sales & Finance analytics foundation matures, extend the same certified-dataset and semantic-layer approach to additional functional domains, sequenced and prioritized jointly with IT and business leadership.\nSupply Chain: inventory, fulfillment, and demand-planning analytics sourced from JDE and related systems.\nManufacturing: production throughput, downtime, and cost/efficiency analytics.\nQuality: defect and scrap trends, supplier quality performance, and corrective-action tracking, drawing primarily on SQL Server-based operational data alongside other source systems.\nData across these domains lives in multiple systems, predominantly SQL-based databases — consistent modeling and reconciliation practices across sources will be essential.\nThis work begins after Sales & Finance foundations are established; exact scope and sequencing will be set collaboratively based on business priority, not assumed to run in parallel from day one.\n\nC) Analytics engineering: data products, semantic layer, and standardized metrics\n\nDesign and own curated analytics datasets and reusable dimensional models that become a “single source of truth” across the functional domains in scope.\nEstablish and enforce consistent KPI definitions via a metrics/semantic layer approach (define metrics once, reuse everywhere).\nImplement testing, documentation, and data-quality practices so stakeholders trust and adopt the analytics outputs.\n\nD) Self-service enablement & analytics democratization\n\nReduce ad-hoc reporting by delivering certified datasets, reusable templates, and clear consumption patterns that allow business users to self-serve safely.\nEstablish training/enablement (office hours, best-practice templates, “how to use” documentation) and analytics community rituals.\n\nE) Contribute to the Analytics Community of Practice\n\nContribute to the design of an Analytics COE operating model — one focused on standards, adoption, and scalable enablement rather than report-factory or help-desk patterns.\nPartner with IT leadership to help shape and execute a 12 to 18-month roadmap for analytics capabilities across the domains in scope (platform patterns, data products, priority areas, adoption metrics).\n\nF) Modern tooling & innovation (governed)\n\nImplement analytics CI/CD patterns (e.g., version control, release discipline, peer review) to scale reliably.\nApply AI-assisted techniques (e.g., anomaly detection, driver analysis, AI-assisted query or code generation) to accelerate analytics delivery where they improve time-to-insight and adoption.\nWork within an AI-enabled analytics environment, including enterprise-grade AI tooling already in use across EMG IT, governed under our Group Responsible AI Policy (accountability, fairness, reliability, transparency).\n\nQUALIFICATIONS\n\nThe requirements listed below are representative of the knowledge, skills, and/or abilities required for this position.\n\nEducation and/or Experience:\n\n8–10+ years in analytics/BI/data roles with evidence of business impact and cross-functional partnership.\nPrior experience directly managing or supervising technical staff (e.g., a data engineer or analyst) is required — this role has a formal direct report.\nExpert SQL + strong data modeling (facts/dimensions; performance-aware).\nProven ability to create reusable analytics assets (certified datasets, metric definitions, semantic consistency) that generalize across business domains, not just one function.\nStrong business acumen and ability to proactively propose analyses (not just take requirements).\nExposure to supply chain, manufacturing, or quality analytics is a plus but not required — Sales & Finance domain depth is the priority for this hire; other domains will be learned on the job as scope expands.\nWorking knowledge of Python for data automation, scripting, and analysis is a plus. Deep statistical or machine learning expertise is not required for this role.\nComfort applying AI-assisted techniques (e.g., anomaly detection, driver analysis, AI-assisted query/code generation) to accelerate analytics work is a plus — willingness to learn is sufficient; deep AI/ML expertise is not required.\n\nWhat success looks like (6 months)\n\nA Sales & Finance revenue analytics capability that integrates non-ERP signals and is actively used by Sales leadership for pricing/revenue decisions.\nMeasurable reduction in ad-hoc reporting through certified datasets, templates, and defined intake/triage patterns.\nA well-managed, productive direct report with clear goals and growth plan in place.\nActive contribution to a functioning Analytics Community of Practice with an agreed 12–18-month roadmap and adoption goals.\nA scoped, prioritized plan (not full delivery) for Supply Chain, Manufacturing, and Quality analytics expansion.\n\nComputer Skills\n\nProficiency in MS Office.\nStrong relational database knowledge is a must, including hands-on experience with MS SQL Server and dimensional/star-schema modeling — the majority of source data across functional domains resides in SQL-based systems.\nExperience with Power BI and Analysis Services development (measures, semantic models, DAX) strongly preferred.\nExperience with Microsoft Fabric (Lakehouse, Data Pipelines, OneLake) and/or Azure Data Factory for data ingestion and transformation strongly preferred. Microsoft Certified: Fabric Analytics Engineer Associate or equivalent is a plus. Candidates without direct Fabric experience but with strong dimensional modeling and cloud data platform fundamentals (e.g., Snowflake, Databricks) are encouraged to apply — Fabric-specific tooling can be learned on the job.\nKnowledge of SSIS, stored procedures, triggers, and performance tuning.\nFamiliarity with legacy enterprise BI tools (SAP Business Objects, Cognos, QlikView) is a plus for supporting existing reporting during migration, but is not a primary requirement.\nExperience with JD Edwards (JDE) Enterprise One or similar ERP-sourced reporting environments is highly desirable, particularly for future Supply Chain and Manufacturing analytics work.\nStrong knowledge and experience in the Software Development Life Cycle; SCRUM experience and certification is a plus.\n\nLanguage Ability\n\nFor business and safety reasons, ability to write reports and business correspondence in English and effectively present information and respond to questions from groups of managers, clients, customers, technicians, and assemblers in English.\n\nPHYSICAL DEMANDS\n\nPhysical demands described are representative of those that must be met by an employee to successfully perform the essential functions of the job.\n\nWhile performing the functions of this position, the employee is frequently required to sit, stand, walk, stoop and kneel; use hands, reach with hands and arms; communicate clearly and effectively. The employee may also be frequently required to lift up to 10 pounds.\n\nWORK ENVIRONMENT\n\nThe work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this position.\n\nThe noise level in the work and shop environment is moderate to loud.\n\nWhile performing the duties of this position the employee may occasionally be required to work near fumes or airborne particles and toxic or caustic chemicals. The employee may also be required to work near moving mechanical parts.\n\nWe are the ASSA ABLOY Group\nOur people have made us the global leader in access solutions. In return, we open doors for them wherever they go. With nearly 63,000 colleagues in more than 70 different countries, we help billions of people experience a more open world. Our innovations make all sorts of spaces – physical and virtual – safer, more secure, and easier to access.\n\nAs an employer, we value results – not titles, or backgrounds. We empower our people to build their career around their aspirations and our ambitions – supporting them with regular feedback, training, and development opportunities. Our colleagues think broadly about where they can make the most impact, and we encourage them to grow their role locally, regionally, or even internationally.\n\nAs we welcome new people on board, it’s important to us to have diverse, inclusive teams, and we value different perspectives and experiences.","datePosted":"2026-08-31T10:59:35.888Z","dateModified":"2026-08-31T10:59:35.888Z","hiringOrganization":{"@type":"Organization","name":"ASSA ABLOY","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Phoenix","addressRegion":"AZ","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"3cc45c475367f9810fc01624"},"url":"https://jobsearcher.com/jobs/3cc45c475367f9810fc01624"}}