Data Engineer Senior

About the role

Acuity Inc. (NYSE: AYI) is a market-leading industrial technology company. We use technology to solve problems in spaces, light and more things to come. Through our two business segments, Acuity Brands Lighting (ABL) and Acuity Intelligent Spaces (AIS), we design, manufacture, and bring to market products and services that make a valuable difference in people’s lives.

We achieve growth through the development of innovative new products and services, including lighting, lighting controls, building management solutions, and an audio, video and control platform. We focus on customer outcomes and drive growth and productivity to increase market share and deliver superior returns. We look to aggressively deploy capital to grow the business and to enter attractive new verticals.

Acuity Inc. is based in Atlanta, Georgia, with operations across North America, Europe and Asia. The Company is powered by approximately 13,000 dedicated and talented associates. Visit us at

Job Summary

Acuity is seeking a

Senior Data Engineer to join the Digital Center of Excellence (DCoE) in Cork and design, build, and support trusted data pipelines and lakehouse data products using Databricks and Azure Data Lake.

The role delivers production-quality ETL/ELT solutions that integrate enterprise data and make curated information available for reporting, analytics, data science, AI, and downstream applications. The ideal candidate is hands-on, quality-focused, and comfortable partnering with architects, analysts, and business subject-matter experts.

Key Tasks & Responsibilities (Essential Functions)

Data Pipeline Engineering

• Design, build, and optimize scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, Delta Lake, and Azure services.
• Ingest data from databases, APIs, files, SaaS applications, and event sources using appropriate batch or streaming patterns.
• Build bronze, silver, and gold datasets using reusable, metadata-driven, and configuration-driven engineering approaches.
• Implement incremental processing, schema evolution, error handling, restorability, reconciliation, and audit controls.

Data Quality & Analytics Enablement

• Apply data-quality rules, testing, lineage, and monitoring to deliver trusted data products.
• Partner with architects, analysts, and business teams to define source-to-target mappings, business rules, and acceptance criteria.
• Curate performant datasets for Power BI, enterprise reporting, analytics, data science, AI, and downstream applications.
• Tune pipelines, SQL, Spark workloads, storage, and table design for reliability, performance, and cost.

Agile Delivery & Operations

• Use Git and Azure DevOps for backlog management, user stories, branching, pull requests, CI/CD, releases, and traceability.
• Create unit, integration, and reconciliation tests and participate in design and code reviews.
• Monitor production pipelines, resolve incidents, perform root-cause analysis, and document operational procedures.
• Contribute reusable components, engineering standards, mentoring, and continuous improvement across the DCoE data team.

Skills and Minimum Experience Required

• 5-6+ years of hands-on data engineering experience building production data pipelines and data products.
• Strong experience with Databricks, Azure Data Lake, Delta Lake, Python/PySpark, and SQL.
• Deep understanding of ETL/ELT, data integration, lakehouse architecture, and bronze/silver/gold design patterns.
• Experience with data quality, reconciliation, schema management, orchestration, performance tuning, and production support.
• Good understanding of reporting, analytics, and how curated data is consumed by Power BI or similar BI tools.
• Working experience with Agile delivery, Git, CI/CD, DevOps practices, and Azure DevOps.
• Bachelor’s degree in computer science, information systems, engineering, or a related field, or equivalent practical experience.

Qualifications & Experience

• Databricks or Microsoft Azure certification.
• Experience with supply chain, manufacturing, ERP, operations, or industrial datasets.
• Experience with streaming, Unity Catalog, metadata-driven frameworks, data governance, or AI/ML data preparation.

Engineering: Databricks, Python/PySpark, SQL, Delta Lake

• Data platform: Azure Data Lake, lakehouse architecture, bronze/silver/gold patterns
• Quality & operations: testing, reconciliation, lineage, monitoring and production support
• Delivery: Git, Azure DevOps, CI/CD, Agile and DevOps practices

Soft Skills

• Strong analytical and structured problem-solving skills.
• Clear communication across technical and business audiences.
• A collaborative, ownership-focused approach to delivery.
• Ability to balance quality, speed, maintainability, and operational needs.
• Ability to mentor engineers and raise standards through design reviews, code reviews, and reusable engineering practices.

Pay and benefits

The compensation is $X EUR. Acuity offers generous benefits including health care, dental coverage, vision plans, 401K benefits, and commissions/incentive compensation depending on the role. For a list of our benefits,

Please click here and here for more information.

Any unsolicited resumes sent to Acuity Inc. from a third party, such as an Agency recruiter, including unsolicited resumes sent to an Acuity Inc. mailing address, fax machine or email address, directly to Acuity Inc employees, or to Acuity Inc. resume database will be considered Acuity Inc. property. Acuity Inc. will NOT pay a fee for any placement resulting from the receipt of an unsolicited resume.

Acuity Inc. will consider any candidate for whom an Agency has submitted an unsolicited resume to have been referred by the Agency free of any charges or fees. This includes any Agency that is an approved/engaged vendor but does not have the appropriate approvals to be engaged on a search.