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# Manager, Data Engineering

- **Company:** CubeSmart
- **Location:** Malvern, PA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Microsoft Access, Artificial Intelligence, Data Analysis, Audit Trail, Microsoft Azure, Software Code Optimization, Continuous Delivery, Data as a Services, Data Architecture, Information Engineering, DevOps, Disaster Recovery, Distributed Computing Environment, IT Management, Python (Programming Language), Machine Learning, Metadata, SQL Azure, DataOps, SQL Databases, Enterprise Data Management, Cloud Platform System, Data Ingestion, Azure Data Factory, Agentic-AI, Data Lakes, Pyspark, Information Technology, Data Analytics, Data Management, Cloud Optimization, Data Pipelines, Databricks
- **Published:** October 20, 2026
- **Apply:** https://www.juju.com/job/15_5cf01a40

## About the Role

* Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
 * 7+ years of experience in data engineering, data platforms, or related technology disciplines, including experience leading engineering teams.
 * Proven ability to develop talent, build accountability, and foster a collaborative, high-performing culture.
 * Strong hands-on experience with SQL, Python, PySpark, and modern data engineering practices.
 * Experience designing, building, and operating modern cloud data platforms and lakehouse architectures, with hands-on experience in Databricks.
 * Experience delivering Databricks-based data engineering solutions, including data ingestion, transformation, orchestration, governance, and production operations.
 * Strong understanding of data architecture, modeling, distributed data processing, data quality, security, governance, scalability, and production operations.
 * Experience enabling AI, Machine Learning, Analytics, and Reporting workloads through enterprise data platforms, with an understanding of the data and engineering capabilities required to support AI-driven solutions.
 * Experience leading teams using Agile delivery practices in a fast-paced environment.
 * Excellent communication, problem-solving, and decision-making skills, with the ability to translate complex technical concepts into business value., * Experience with the Databricks Lakehouse Platform, including Delta Lake, Unity Catalog, AI agents, Apps, and related platform capabilities.
 * Experience enabling modern AI and analytics use cases, including conversational analytics, semantic-layer experiences, AI agents, and business-facing data applications.
 * Experience with Microsoft Azure data services, including Azure Data Factory and Azure SQL.
 * Experience implementing CI/CD, DataOps, and DevOps practices for data platforms and products.
 * Experience with cloud cost optimization and FinOps practices.
 * Understanding of Machine Learning lifecycle management and AI-enabled analytics.
 * Master's degree and/or relevant cloud, data, AI, or Databricks certifications.

We are an Equal Opportunity Employer, Minority/Female/Veteran/Individuals with Disabilities/Sexual Orientation/Gender Identity.

## Description

* Lead, coach, and develop a high-performing Data Engineering team through hiring, mentoring, career development, and performance management.
 * Advance strategy, roadmap, and evolution of CubeSmart's cloud data platform, enabling Analytics, Reporting, Data Science, Machine Learning, AI, and other enterprise data capabilities.
 * Drive adoption of the enterprise data platform through self-service analytics, trusted data products, conversational analytics, and AI agents that enable faster, data-informed decision-making.
 * Evaluate emerging cloud, data, and AI technologies and identify opportunities to modernize, automate, and optimize enterprise capabilities.
 * Foster a product-oriented engineering culture focused on delivering reusable, scalable, and business-aligned data products.
 * Provide hands-on technical leadership across the data lifecycle, including architecture, modeling, ingestion, integration, batch and streaming pipelines, data quality, metadata and lineage, governance, and delivery of trusted data products.
 * Define and implement platform controls for security, access, auditability, disaster recovery, resiliency, compliance, and operational risk
 * Partner with IT leadership and strategic vendors on platform optimization, cost management, and technology investments.
 * Communicate architecture decisions, technical tradeoffs, risks, and business impact effectively to both technical and non-technical audiences.