All fields marked * are required
Key Responsibilities
● Design, develop, and maintain scalable data transformation pipelines using SQL, dbt, and Jinja templating.
● Build and optimize dimensional data models in dbt to support analytics, reporting, and BI consumption.
● Collaborate with Product, Analytics, and BI teams to translate business requirements into robust analytical data models.
● Perform exploratory data analysis (EDA) using SQL, Excel, and other analytical tools to validate business requirements and uncover insights.
● Enhance and maintain analytics engineering codebases, including dbt models, macros, packages, tests, and documentation.
● Implement data quality frameworks, automated testing, and governance-aligned transformation logic.
● Optimize SQL workloads and analytical queries through partitioning, clustering, materialization strategies, and performance tuning techniques.
● Ensure consistency of business metrics, semantic definitions, and data logic across dashboards and reporting platforms.
● Apply software engineering best practices, including version control, code reviews, CI/CD pipelines, and automated deployments.
● Participate in Agile development processes and collaborate effectively with global and offshore teams to ensure high-quality delivery.
Required Qualifications
● Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
● 8+ years of experience in analytics-focused data engineering or analytics engineering roles.
● 3+ years of hands-on experience with dbt, including advanced model development, macros, packages, testing, and deployment.
● Strong expertise in dimensional modeling, data warehousing concepts, and analytics data architecture.
● Advanced SQL skills with proven experience in query optimization and performance tuning for large-scale datasets.
● Experience working with modern cloud data platforms such as Snowflake and Amazon Redshift.
● Familiarity with Python and Jinja templating for analytics engineering and automation use cases.
● Experience implementing data governance, privacy controls, data quality standards, and access management requirements.
● Strong understanding of Agile methodologies and experience working in distributed team environments.
● Excellent problem-solving skills, attention to detail, and a strong ownership mindset focused on building clean, reliable, and trusted data assets.
Preferred Qualifications
● Experience in Sports, Media, Entertainment, Digital Marketing, or Consumer Analytics domains.
● Exposure to modern BI and visualization platforms such as Tableau, Power BI, or Looker.
● Understanding of customer engagement, audience analytics, campaign measurement, and digital product analytics.
● Experience working with large-scale event, clickstream, or behavioral datasets.
Required
Preferred
All fields marked * are required
Key Responsibilities
● Design, develop, and maintain scalable data transformation pipelines using SQL, dbt, and Jinja templating.
● Build and optimize dimensional data models in dbt to support analytics, reporting, and BI consumption.
● Collaborate with Product, Analytics, and BI teams to translate business requirements into robust analytical data models.
● Perform exploratory data analysis (EDA) using SQL, Excel, and other analytical tools to validate business requirements and uncover insights.
● Enhance and maintain analytics engineering codebases, including dbt models, macros, packages, tests, and documentation.
● Implement data quality frameworks, automated testing, and governance-aligned transformation logic.
● Optimize SQL workloads and analytical queries through partitioning, clustering, materialization strategies, and performance tuning techniques.
● Ensure consistency of business metrics, semantic definitions, and data logic across dashboards and reporting platforms.
● Apply software engineering best practices, including version control, code reviews, CI/CD pipelines, and automated deployments.
● Participate in Agile development processes and collaborate effectively with global and offshore teams to ensure high-quality delivery.
Required Qualifications
● Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
● 8+ years of experience in analytics-focused data engineering or analytics engineering roles.
● 3+ years of hands-on experience with dbt, including advanced model development, macros, packages, testing, and deployment.
● Strong expertise in dimensional modeling, data warehousing concepts, and analytics data architecture.
● Advanced SQL skills with proven experience in query optimization and performance tuning for large-scale datasets.
● Experience working with modern cloud data platforms such as Snowflake and Amazon Redshift.
● Familiarity with Python and Jinja templating for analytics engineering and automation use cases.
● Experience implementing data governance, privacy controls, data quality standards, and access management requirements.
● Strong understanding of Agile methodologies and experience working in distributed team environments.
● Excellent problem-solving skills, attention to detail, and a strong ownership mindset focused on building clean, reliable, and trusted data assets.
Preferred Qualifications
● Experience in Sports, Media, Entertainment, Digital Marketing, or Consumer Analytics domains.
● Exposure to modern BI and visualization platforms such as Tableau, Power BI, or Looker.
● Understanding of customer engagement, audience analytics, campaign measurement, and digital product analytics.
● Experience working with large-scale event, clickstream, or behavioral datasets.
Required
Preferred