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Location
: Canada – RemoteCompensation - $130,000-$150,000 CADOverview / ObjectiveWe are seeking an Analytics Data Engineer to join our client's Sports Analytics Engineering Practice.
This role is focused on turning ingested data into trusted, high-value analytical assets that power dashboards, insights, and decision-making across digital products, marketing, and fan engagement.
You will own the analytics layer of the data platform, building dimensional models and transformation logic that serve as a single source of truth for analysts, data scientists, and BI teams. Key ResponsibilitiesDesign and build scalable data transformation pipelines using SQL, DBT, and Jinja templatingDevelop and maintain dimensional data models optimized for analytics and BI consumptionOwn the analytics data layer in DBT, enabling self-service analytics for business usersCollaborate with product, analytics, and BI teams to translate business
requirements
into data modelsEnhance and maintain analytics codebases including DBT models, macros, tests, and documentationImplement data quality checks, tests, and governance-aligned transformationsOptimize SQL for performance using partitioning, clustering, and materialized viewsEnsure semantic consistency and metric definitions across dashboards and reportsApply software engineering best practices including version control, CI/CD, and peer code reviewsSupport Agile development and collaborate with offshore teams for delivery and reviewsRequired
Qualifications
Bachelors or Masters degree in Computer Science, Statistics, Mathematics, or a related field5+ years of experience in analytics-focused data engineering3+ years of deep hands-on experience with DBT, including advanced models, macros, and packagesStrong expertise in dimensional modeling and data warehousing conceptsProficiency in SQL performance tuning and large-scale analytical query optimizationExperience working with Amazon Redshift and modern cloud data platformsFamiliarity with Python and/or Jinja templating for analytics engineeringExperience aligning data models with governance, privacy, and access-control
requirements
Agile experience and comfort working with extended offshore teamsStrong ownership mindset, attention to detail, and passion for building clean, trusted data products.
Analytics Data Engineer
JOB SUMMARY
Job details
Location
: Canada – RemoteCompensation - $130,000-$150,000 CADOverview / ObjectiveWe are seeking an Analytics Data Engineer to join our client's Sports Analytics Engineering Practice.
This role is focused on turning ingested data into trusted, high-value analytical assets that power dashboards, insights, and decision-making across digital products, marketing, and fan engagement.
You will own the analytics layer of the data platform, building dimensional models and transformation logic that serve as a single source of truth for analysts, data scientists, and BI teams. Key ResponsibilitiesDesign and build scalable data transformation pipelines using SQL, DBT, and Jinja templatingDevelop and maintain dimensional data models optimized for analytics and BI consumptionOwn the analytics data layer in DBT, enabling self-service analytics for business usersCollaborate with product, analytics, and BI teams to translate business
requirements
into data modelsEnhance and maintain analytics codebases including DBT models, macros, tests, and documentationImplement data quality checks, tests, and governance-aligned transformationsOptimize SQL for performance using partitioning, clustering, and materialized viewsEnsure semantic consistency and metric definitions across dashboards and reportsApply software engineering best practices including version control, CI/CD, and peer code reviewsSupport Agile development and collaborate with offshore teams for delivery and reviewsRequired
Qualifications
Bachelors or Masters degree in Computer Science, Statistics, Mathematics, or a related field5+ years of experience in analytics-focused data engineering3+ years of deep hands-on experience with DBT, including advanced models, macros, and packagesStrong expertise in dimensional modeling and data warehousing conceptsProficiency in SQL performance tuning and large-scale analytical query optimizationExperience working with Amazon Redshift and modern cloud data platformsFamiliarity with Python and/or Jinja templating for analytics engineeringExperience aligning data models with governance, privacy, and access-control
requirements
Agile experience and comfort working with extended offshore teamsStrong ownership mindset, attention to detail, and passion for building clean, trusted data products.
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