Analytics Engineers (Business Intelligence Developers) sit at the intersection between business users, BI analysts and Data Engineering/Data Scientists. They are responsible for creating robust, reusable, efficient, and high quality data models & data transformations for data analytics. They play an important role in improving ease of analytics, reducing time to insights for the end users, and improving time-to-actions to maximize business impacts in our data-driven organization.

Responsibilities

  • Collaborate with business teams and BI team members to collect business requirements, design successfully analytics outcomes, and implement scalable and high quality data models and data flows
  • Expand our constantly growing data platform with high quality data transformation pipelines using dbt / SQL.
  • Reduce time-to-insight and improve ease-of-analytics by enabling and expanding more data models in our self-service data mart, and other self-service BI tools in the organization.
  • Using metadata analytics, SQL profiling & other tools to find room to improve and optimize data analytics platform usage & efficiency
  • Craft code that meets best practices for a highly scalable and maintainable data platform. Maintain and advocate for these standards through code review.
  • Improve data quality through profiling, data wrangling and create automated tests to assure data quality, and working with data engineers and product engineers to improve data quality from upstream processes
  • Contribute to the data catalog
  • Participate in query performance tuning to continually improve the performance of data platform

Qualifications

  • Proficiency in SQL, writing efficient, performant and optimized SQLs for complex business logic and data transformations
  • Comfortable working with Git and the command line
  • Proficiency in python will be an absolute advantage
  • Strong working knowledge of data dimensional modeling and data schema design best practices
  • Clear and direct communication skills about complex, technical topics
  • Experience working as part of a data team; preferably as either a data analyst or data engineer.
  • Able to build and maintain multi-functional relationships with various teams across the business