What you will do:

• Understand strategic imperatives of the business and conducts value assessments to support prioritization of opportunities, including initiatives related to the data analytics portfolio through planning, budgeting, stakeholder engagement, risk/issue management, and status reporting.

• Assist in solutions architecture, data engineering, DevOps and analytics related strategic planning activities.

• Lead data engineering from an operational standpoint and provides expert recommendations for data engineering product design and know-how to address business needs.

• Partner with TIS Functional teams in delivery and sustainment of data analytics product needs

• Using an Agile methodology, organize the work efforts of the Data and Analytics teams to ensure all data engineering products, services, and solution enhancement designs align with enterprise architecture direction and standard methodologies and meet customer requests in a timely manner.

• Implement and provides insight to standards, guidelines, and best practices for the data management program.

• Make decisions on moderately complex to highly complex data issues regarding technical approach for project and operational components within the team’s data and reporting framework.

• Act as a liaison between Data and Analytics team and external analytics service providers, partner with business relationship managers, business users, portfolio architects, functional and product owners, data analysts, solution and data architects, and data scientists to identify and develop data engineering use cases with attention to cloud computing (batch, micro-batch, or stream processing) and storage.

• Provide strategic and expert guidance in development of data engineering models and ensures processes and solution components conform to technical functionality (e.g., preparation of high-quality data, security, performance, scalability, data recovery, and reliability)

Who you are:

• You have bachelor’s degree in computer science, Engineering or a related field and 7+ years progressively professional experience in a computer engineering role

• Deep understanding of modern data engineering and big data analytics technologies, including analytical data stores (e.g., Delta tables, Data Lakehouse architecture), performance tuning and optimization, machine learning, advanced visualization, and automation

• Sophisticated level knowledge of relational, NoSQL, or NewSQL database systems; data modeling; and managing structured and unstructured data.

• Experience with scaling data engineering solutions using development tools for CI/CD, unit and integration testing, orchestration.

• Advanced algorithm design and production programming skills in Python, Scala, Kafka, Hive, JavaScript, JQuery, JSON, REST API, and other related coding languages with proven experience using Apache Spark and designing relevant data structures, algorithms, and techniques related to systems that support high volume, velocity, or variety datasets including apps that utilize machine learning and artificial intelligence (ML/AI)

• Technical experience in leading the development of data engineering pipelines using Databricks and integrating them into cloud-based analytical solutions working in collaboration with data ingestion, data engineering, data provisioning, data visualization, and data science teams.

• Understanding of parallel and distributed data processing techniques and platforms (MPI, Map/Reduce, Batch) and systems and cloud infrastructure tools (e.g., Kubernetes, Docker, and Ansible)

• Strong DevOps skillset ranging from but not limited to, software development, IT operations, automation, Cloud computing and monitoring and logging.

Preferred:

• Knowledge of data governance practices, approaches and technology issues and trends related to managing enterprise data and information assets in a large, complex organization.

• Knowledge of Agile development best practices and experience with tools such as GitHub

Enbridge Flex work program

Enbridge provides competitive workplace programs that differentiate us and offer flexibility to our team members. Enbridge’s FlexWork (Hybrid Work Model) offers eligible employees the opportunity to work variable daily schedules with a flexible start and end time, to opt for a compressed workweek schedule, and the option to work from home on Wednesdays and Fridays. Role requirements determine your eligibility for each option or combination of options. #joinourteam #LI-Hybrid