Senior Data Analytics Engineer

ASSA ABLOY is hiring a Senior Data Analytics Engineer to build and operate governed analytics foundations that help Sales and Finance make better decisions on revenue drivers. This role expands quickly in scope: within the first year, you will extend certified datasets, standardized metrics, and a shared semantic layer to supply chain, manufacturing, and quality analytics in an AI-enabled environment, governed under the Group Responsible AI Policy.

What you’ll deliver

• Partner with Sales and Finance to create a differentiated sales analytics product focused on revenue drivers such as pricing/discounting, mix, customer or segment performance, and channel.
• Produce executive-ready insight narratives and repeatable decision frameworks, including driver trees, leading indicators, and KPI hierarchies.
• Integrate and reconcile data beyond ERP by bringing in sources such as customer POS feeds, CRM, external or industry signals, customer master enrichment, and spreadsheets into governed analytical datasets.
• As the foundation matures, extend the same certified-dataset and semantic-layer approach to additional functional domains in a sequence and priority plan developed with IT and business leadership.
• Own domain analytics coverage across:
  • Supply Chain: inventory, fulfillment, and demand-planning analytics sourced from JDE and related systems.
  • Manufacturing: production throughput, downtime, and cost or efficiency analytics.
  • Quality: defect and scrap trends, supplier quality performance, and corrective-action tracking using primarily SQL Server-based operational data plus other systems.

How the analytics ecosystem will work

• Design and own curated analytics datasets and reusable dimensional models that support a single source of truth across functional domains.
• Establish and enforce consistent KPI definitions using a metrics and semantic layer approach, so metrics are defined once and reused everywhere.
• Implement testing, documentation, and data-quality practices to support stakeholder trust and adoption.
• Reduce ad-hoc reporting by delivering certified datasets, reusable templates, and clear consumption patterns that enable business self-service safely.
• Provide training and enablement through office hours, best-practice templates, and “how to use” documentation, supported by analytics community rituals.
• Contribute to an Analytics COE operating model centered on standards, adoption, and scalable enablement rather than report-factory or help-desk patterns.

Engineering practices and AI-enabled execution

• Partner with IT leadership to shape and execute a 12 to 18-month roadmap for analytics capabilities across the in-scope domains, including platform patterns, data products, priority areas, and adoption metrics.
• Implement analytics CI/CD patterns such as version control, release discipline, and peer review to scale reliably.
• Apply AI-assisted techniques (for example anomaly detection, driver analysis, AI-assisted query or code generation) to accelerate time-to-insight and adoption where it improves outcomes.
• Work within an AI-enabled analytics environment using enterprise-grade AI tooling already in place across EMG IT, aligned to the Group Responsible AI Policy (accountability, fairness, reliability, transparency).

What you bring

• 8–10+ years in analytics/BI/data roles with evidence of business impact and strong cross-functional collaboration.
• Required: experience directly managing or supervising technical staff (this role has a formal direct report).
• Expert SQL and strong data modeling (facts/dimensions, performance-aware).
• Proven ability to create reusable analytics assets (certified datasets, metric definitions, semantic consistency) that generalize across domains.
• Strong business acumen and the ability to proactively propose analyses.
• Exposure to supply chain, manufacturing, or quality analytics is a plus; Sales & Finance depth is the priority, with additional domains learned as scope expands.
• Python is a plus for automation, scripting, and analysis.
• AI-assisted techniques experience is a plus (an ability and willingness to learn is sufficient; deep AI/ML expertise is not required).
• Proficiency in MS Office.
• Strong relational database knowledge with hands-on experience in MS SQL Server and dimensional/star-schema modeling, since most source data across domains resides in SQL systems.
• Preferred: experience with Power BI and Analysis Services development (measures, semantic models, DAX).
• Preferred: experience with Microsoft Fabric (Lakehouse, Data Pipelines, OneLake) and/or Azure Data Factory for ingestion and transformation.
• Knowledge of SSIS, stored procedures, triggers, and performance tuning.
• Strong Software Development Lifecycle knowledge; SCRUM experience and certification is a plus.
• Ability for business and safety reasons to write reports and correspondence in English, and effectively present information and respond to questions in English to managers, clients, customers, technicians, and assemblers.

Location: Phoenix, AZ (onsite)

Physical demands and work environment

• Frequently required to sit, stand, walk, stoop, and kneel; use hands and reach with hands and arms; communicate clearly.
• May be frequently required to lift up to 10 pounds.
• Work environment may be moderate to loud; occasional proximity to fumes or airborne particles and toxic or caustic chemicals; may require working near moving mechanical parts.