ASSA ABLOY

Senior Data Engineer

New Haven, Connecticut, USA · Senior · full-time

Sponsorship not specifiedDetected 64 days ago

PythonAlgorithmsSQLDatabricksAzureCI/CDMachine LearningSparkData EngineeringData ScienceData VisualizationCommunicationProblem Solving

About the role

What you will be doing The Senior Data Engineer is a core member of the Data & Analytics team.
This role will be responsible for delivering high-performing, scalable, flexible, and cost-effective cloud-based enterprise business data and analytics solutions.
This position plays a key role in fulfilling the future modern data & analytics strategy for ASSA ABLOY Americas Division.

Architect and implement enterprise-grade, cloud-based data platforms using Azure and Microsoft Fabric.
Design scalable data Lakehouse architectures leveraging Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Microsoft Fabric (Lakehouse, Warehouse, Data Pipelines, Real-Time Analytics).
Develop high-performance ETL/ELT pipelines using Azure Data Factory, Fabric Data Pipelines, SSIS, and PySpark.
Implement distributed data processing solutions using Spark architecture and optimize Spark jobs for performance and cost efficiency.
Lead cloud architecture design, including data ingestion patterns, medallion architecture (Bronze/Silver/Gold), governance frameworks, and CI/CD automation.
Collaborate with cross-functional stakeholders to gather future-state requirements and translate business needs into technical solutions.
Design and optimize complex SQL-based data models, star schemas, and enterprise semantic layers for analytics and reporting.
Support enterprise BI initiatives using Power BI, Fabric Semantic Models, and Power Automate.
Participate in on-call rotations to support mission-critical production systems.
Self-driven professional with excellent communication skills and ability to collaborate across technical and business teams.

To be successful in the position, you must have a great attitude as well as strong business analysis and technical development.
5+ years of deep, hands-on experience with Data Warehouse architecture, dimensional modeling, ETL/ELT frameworks, and enterprise BI solutions.
Advanced programming proficiency in SQL, Python, and PySpark with solid understanding of distributed computing and Spark architecture concepts (execution model, partitioning, optimization strategies).

Working knowledge of modern data platform patterns including lakehouse architecture, medallion layering, data governance, and CI/CD practices.
Experience with Microsoft Power Platform tools including Power BI and Power Automate preferred.
Strong analytical, problem-solving, and troubleshooting skills with the ability to navigate complex enterprise data landscapes.
Bachelor's or Masters degree in Computer Science, Data Science, Information Systems, Engineering, or related field (or equivalent practical experience).

Competitive compensation and benefits package which includes multiple healthcare options, tuition reimbursement, and matching 401k.
Generous holiday schedule and paid time off to refresh and recharge.
Enable advanced analytics use cases using Python, R, machine learning frameworks, and Azure ML services.
Exposure to Data Science and advanced analytics technologies (Python, R, machine learning algorithms, Azure ML) preferred.
Up to 25% travel based on project requirements What we offer We're passionate about providing amazing opportunities and benefits, so that you can enjoy a lifelong career with us.

We are proud to offer: Continuous professional development opportunities and an environment that fosters internal growth and mobility.

ASSA ABLOY is an Equal Opportunity Employer/Minorities/Females/Disabled/Veteran #LI-EL1 #LI-OSA We are the ASSA ABLOY Group Our people have made us the global leader in access solutions.
Equal Opportunity Employer/Minorities/Females/Disabled/Veteran #LI-EL1 #LI-OSA We are the ASSA ABLOY Group Our people have made us the global leader in access solutions.

This listing is sourced directly from ASSA ABLOY's careers page and normalized into a canonical job model.