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Homeoffice Director, Data Engineering at None

None · Remote, United States Of America · Remote

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Job Title:  ISE91J – Director - Data Engineering

 

Brief Description:

 

The Director - Data Engineering will be responsible for overseeing the build and delivery of data projects. This role leads a team of experienced Data Warehouse Engineers, ensuring that projects are delivered on time, with high quality. The role involves building partnerships with cross-functional teams, managing and communicating effectively with stakeholders, and strict adherence to UBC Agile DevOps best practices.

 

Primary Responsibilities:

 

  • Work with Senior Leadership and stakeholders to define and execute the long-term vision and strategic roadmap for the enterprise data warehouse.
  • Lead and manage end-to-end delivery of backend data projects, ensuring timely, quality delivery.
  • Lead technical data discussions with enterprise teams and stakeholders.
  • Develop and maintain detailed project plans, including management of resource allocation, budgets, and timelines.
  • Coordinate with product owners, developers, Quality Assurance (QA), and stakeholders to ensure alignment and successful execution of project objectives.
  • Serve as the primary point of contact for external clients and internal business partners, providing proactive verbal and written updates, managing expectations, and addressing any issues or concerns.
  • Ensure high quality of data project deliverables through comprehensive testing and adherence to Agile DevOps workflow processes.
  • Build and optimize an agile, collaborative, high-performing Data Engineering team, encouraging continuous improvement and innovation.
  • Identify and resolve technical and project-related barriers.
  • Oversee project budgets.
  • Implement data engineering best practices, staying updated on latest industry trends and technologies.
  • Mentor and develop Data Engineers, providing guidance and support to promote professional growth and team culture.
  • Provide technical expertise and coaching to Data Engineers during design, code review, and troubleshooting working sessions.
  • Oversee the design, development, and implementation of data pipelines for data ingestion, transformation and delivery using SAS, R, and/or Python depending on project needs.

 

Required Qualifications:

 

  • Bachelor’s or Master’s Degree in Data Engineering, Computer Science, Information Technology, Business or a related field.
  • 10+ years experience leading a data engineering team.
  • Significant experience in technical data project management with a proven track record of successful delivery.
  • Expertise in data integration techniques, including ETL/ELT processes and data pipelines.
  • Understanding of data modelling techniques. E.g. hierarchical, relational, entity-relationship (ER)
  • Significant experience with Snowflake as a relational database systems (RDBMS).
  • Proficient with SQL.
  • Extensive knowledge of data governance principles, data quality management, and data privacy regulations.
  • Strong understanding of software development lifecycle (SDLC) and Agile methodologies.
  • Strong experience working in projects with Agile/Scrum methodologies.
  • Excellent leadership and team management skills with the ability to motivate and guide a team of Data Engineers.
  • Exceptional communication and interpersonal skills, with the ability to engage effectively with technical and non-technical stakeholders.
  • Analytical and problem-solving abilities with strong attention to detail.
  • Experience managing budgets and resource allocation.
  • Data architecture experience.
  • Experience working with APIs and a multitude of data source formats including JSON and XML.
  • Proficient with SAS, R, and Python.
  • Experience with data tokenization.

 

Preferred Qualifications:

 

  • Proficient in project management tools and software.
  • PMP or other project management certification desirable.
  • Significant experience with SQL Server Integration Services (SSIS).
  • Experience with Azure Data Factory.
  • Experience with AI tools to enhance data engineering services.
  • Experience working with healthcare data exchanges using FHIR and HL7 standards.
  • Well-versed in HIPAA and GDPR compliance standards.
  • Background working with Real World Data (RWD).

 

Supervisory Responsibilities:

  • 4-6 Data Warehouse Engineers
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