Analytics Engineer

<h3>📋 Description</h3> • Partner with Data Engineering to build and optimize robust data pipelines that ensure data accessibility and reliability. Collaborate with Business Intelligence to implement crucial business logic that powers BI dashboards, directly impacting key business decisions and providing broad organizational exposure. • Experience in designing and implementing data transformation workflows using best practices in data modeling, ELT processes, and ensuring data quality and consistency for analytical use cases. • Design and implement complex data transformation logic primarily in SQL with a focus on creating reusable data models that support various analytical needs. Build and maintain dbt models to ensure data accuracy, consistency, and reliability. • Collaborate with data engineers, data analysts, and business stakeholders to understand data requirements, define key metrics, and deliver actionable insights through data models and reporting solutions. • Implement and maintain data quality checks and validation processes to ensure the accuracy and reliability of data used for analysis. Develop comprehensive documentation of data models, and transformation logic to facilitate data understanding. • Develop and manage CI/CD pipelines to automate and streamline the deployment of data solutions. Ensure that data workflows are thoroughly tested, integrated, and deployed efficiently, following best practices for version control, automation, and quality assurance. • Contribute to and uphold data governance principles, such as data lineage and data cataloging, to improve data discoverability, usability, and trust for analytical purposes. • Stay current with emerging analytical techniques, data modeling best practices, and analytics engineering trends. Contribute to a data-driven culture through collaboration and knowledge sharing. • On-call rotation support, the on-call is shared across Analytics and Data Engineering teams. <h3>🎯 Requirements</h3> • 3+ years of experience in an Analytics Engineering, Data Engineering, or data-oriented software engineering role creating and pushing end-to-end data engineering pipelines. • Graduate degree in a quantitative field: Computer Science, Mathematics, Statistics, Business Analytics, Engineering) or equivalent experience. • Experience building and optimizing data pipelines for analytics, with a focus on data transformation and modeling. • Experience in integrating data from various sources to support analytical needs, including familiarity with data warehousing principles and ELT processes. • Experience in most of the following: • ELT tools: dbt • SQL/NoSQL databases/warehouses: Postgres, BigQuery, BigTable, etc • Replication Services: Data Stream, Rudderstack, Hevo, Kafka, etc. • Scripting languages: SQL, Python, Go. • Familiarity with cloud platform data services, such as data warehousing solutions (e.g., BigQuery, Snowflake, Redshift) and storage (e.g., Cloud Storage, S3). • Code version control: Git • Data pipeline and workflow tools relevant to analytics: Dataform, Spark, and orchestration tools used in data analytics workflows (e.g., Argo Workflows, Airflow, cloud-based workflow services). • Data visualization and BI tools knowledge (e.g., Tableau, Looker). • Excellent organizational, communication, presentation, and collaboration experience with organizational technical and non-technical teams • Strong experience in dimensional modeling, data warehousing, and data mart design. • Ability to translate business questions into data requirements and analytical solutions. • Experience with data quality standards and data governance principles. • Preferred: experience in a daily fantasy sports platform or a similar data-intensive analytical environment, with a proven track record of delivering impactful data insights. <h3>🏖️ Benefits</h3> • Company-subsidized medical, dental, & vision plans • 401(k) plan with company match • Annual bonus • Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!) • Generous paid leave programs, including 16-week paid parental leave and disability benefits • Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked • Company-wide in-person events and team outings • Lifestyle enhancement program • Company equipment provided (Windows & Mac options) • Annual performance reviews with opportunities for growth and career development