Data Engineer

Description:

At CubeSmart, we’re intentional about culture. You can experience it everywhere from our mission statement of “genuine care” to our “It’s What’s Inside That Counts” tagline to calling each other “teammates” rather than employees. This spirit fosters a fun and collaborative environment that has resulted in our rapid growth and being recognized amongst the top in our industry.

CubeSmart’s award-winning team is made up of people who genuinely care. Teammates care about our customers and the life events and/or business needs they are facing. Teammates are passionate, responsible and understanding. The CubeSmart team is made up of people who have a can-do attitude, are committed to their own success and the success of the company, and lead by example.

If this sounds like a team and culture that matches your personal values and motivations, we want to hear from you.

Responsibilities

This role will also be responsible for the development and maintenance of ETL processes that manage the consumption of data by CubeSmart’s core systems. The role will serve as a technical expert to analyze the needs of CubeSmart’s applications and business data requirements and produce an optimal solution according to their needs and specifications, and in alignment with CubeSmart’s data design standards. This individual will be part of the team building a data and analytics platform in the Microsoft Azure cloud to support the CubeSmart business. This will include designing and building the data ingestion and ETL pipelines to create the cloud Lakehouse environment. In addition, this person will be engaged to develop features in the legacy SQL Server Data Warehouse platform.

Responsibilities
 

• Collaborate with program manager(s), application development, and data consumers to develop data ingestion and ETL pipelines required to enable CubeSmart data consumers to onboard processes to the Data Lakehouse platform
• Create database designs, stored procedures, views and other associated database objects required to implement processes in support of application development efforts
• Design and development of data pipelines and ETL processes required to support system integration and application development needs in the legacy SQL data warehouse environment
• Identification and implementation of database performance tuning required to validate that all systems are performing to an optimal level
• Collaborate with 3rd party vendors to understand externally sourced data and incorporate into CubeSmart’s data environment, in adherence with CubeSmart’s data design standards
• Bachelor’s degree in Computer Science, Information Technology or a related discipline
• Strong skills in SQL, Python, and PySpark
• Experience with Microsoft Azure data services (Azure Data Factory, Azure Databricks, Azure SQL, and Databricks ML Flow) or equivalent is preferred
• Full understanding of the Software Development Life Cycle (SDLC) and experience with Agile software development processes
• Solid understanding of cloud DevOps capabilities, preferably Azure DevOps
• Experience with MongoDB (or similar non-relational database platform) or PostgreSQL is a plus
• Experience supporting databases and data models for ERP or financial systems in a plus
   

Qualifications

Knowledge, Skills, Abilities and Personal Characteristics
 

• Service orientation towards business-focused 24×7 support and service mentality
• Ability to work within a team environment, showing an openness to collaborate with technical and business peer, with the ability to step up and take on new challenges in response to changing business conditions
• Ability to learn quickly, adapt work processes to adhere with best practices
• Ability to clearly convey technical information to both technical and non-technical audiences
• Collaborative individual who creates open channels of communications and encourages technical dialogue across the department.
• Well-developed analytical and problem-solving abilities
• Ability to work on multiple tasks and projects at once, with the ability to properly prioritize one’s own work and the work of others