Analytics Engineer
Job details
We seek an experienced and ambitious Analytics Engineer to join our cross-functional data team and help shape our data models and analytical frameworks. This role supports advanced business intelligence, analytics, and AI-driven insights at Superside. Superside operates at the intersection of creative services, technology, and product development. This unique position allows us to build scalable, well-structured data models representing some of the most intriguing and novel data relating to creative performance and AI. We empower internal teams and drive the development of data-driven products, creating new market opportunities. Reporting to the Head of Data & Analytics, you will collaborate closely with data engineers, developers, business analysts, and operational teams to define and implement our data modeling strategy and analytics infrastructure. What you'll do
- Develop and maintain well-documented, scalable, and performant data models using dbt, ensuring business data is well structured, logically modeled, rich in analytical value, and ready for analysis.
- Design and optimize SQL-based transformation pipelines that deliver high-quality, analytics-ready datasets to business intelligence and analytics teams.
- Collaborate with business analysts, product managers, and stakeholders to gather requirements and ensure data models support accurate and meaningful business reporting.
- Implement and embed business logic within data models to ensure KPIs and other business metrics accurately reflect the datasets.
- Establish and maintain data quality checks, automated testing, and documentation to ensure business-critical data accuracy, consistency, and reliability.
- Continuously monitor and improve the performance of data transformations and queries, optimizing them for speed, efficiency, and scalability.
- Maintain clear and comprehensive documentation for data models, business logic, and data flows, ensuring that analysts and stakeholders can easily use the data.
- Assist in mentoring junior team members on best practices in analytics engineering and actively contribute to developing the team’s skills and capabilities.
- Fluency in SQL, with experience writing efficient and scalable queries to transform, model, and analyze large datasets.
- Experience with data modeling tools like dbt to build and manage structured, reusable data models.
- Ability to translate business requirements into well-defined and scalable data models, ensuring alignment with key business metrics.
- Familiarity with BI tools such as Looker, Tableau, or Power BI and a strong understanding of structuring data for optimal use in these platforms.
- Experience implementing automated data quality checks and tests within data pipelines to maintain data integrity; some Python experience is advantageous.
- Strong communication skills and the ability to collaborate with technical and non-technical stakeholders to gather requirements and deliver data solutions that meet business needs.
- A basic understanding of cloud-based data platforms like Snowflake, BigQuery, or Redshift is beneficial.
- Experience working in a remote-first, collaborative environment, demonstrating a proactive and self-directed work approach.
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