About the role

Data Engineer at Alberta Blue Cross designing and implementing data solutions for business analytics. Collaborating on data pipelines and analytics projects in a hybrid work environment.

Responsibilities

Work collaboratively with multiple teams across the organization.
Communicate effectively with your team, team manager and business customers.
Engineer data pipelines and BI/DW solutions to enable business analytics and insights.
Work with and lead cross functional teams on designing, building, and optimizing data systems.
Translate business rules and requirements into data objects, data models, source to target mappings and write abstracted, reusable code components.
Facilitate technical meetings with stakeholders, and advise technical option analyses based on leading practices in language understandable by stakeholders.
Assess the root cause of issues, recommend changes, and resolve issues.
Perform systems testing with both IT and business customers.
Provide support during various phases of testing.
Review requirements with users and provide time estimates for task completion.
Work as part of a project team as required.
Follow IT Controls practices (e.g. IT Governance, Data Privacy) to ensure quality output.
Follow Information Life Cycle and Data Governance best practices.
Embrace continual learning and understanding of the application environment, interdependencies, and data and systems integrations.

A bachelor’s degree or diploma in Computer Science or related technical discipline.
3+ years of progressive experience with analysis, design, development, testing, and deployment.
3+ years of experience implementing distributed systems and data architecture-design and implement batch and stream data processing pipelines.
Experience working with and building data pipelines, applications to stream and process datasets at low latencies leveraging Databricks and Python.
Experience with ETL development tools (e.g. Talend, Informatica, Databricks).
Applied knowledge of data storage and BI technologies such as Data Lakes, Data Warehouse, and Data Lakehouses.
Ability to write efficient, complex SQL queries against very large data sets, perform ETL optimizations, and work with big data processes.
Exceptional consultation skills, with the ability to convey technical ideas to both technical and non-technical audiences.
Exceptional planning, organizational, analytical, and problem-solving skills.
Leadership skills to create positive, respectful, and productive working relationships with all types of stakeholders.
The ability to think outside the box to solve complex problems.