Senior Analytics Engineer, Arcadia

• 4+ years as an Analytics Engineer or equivalent role; experience with dbt is strongly preferred
• 6+ years, cumulatively, in the data space (data engineering, data science, analytics, or similar)
• Expert-level understanding of conceptual data modeling and data mart design
• An understanding of data structures and/or database design plus deep experience with SQL and Python
• Experience building data pipelines and database management including Snowflake or similar
• Ability to bring a customer-oriented and empathetic approach to understanding how data is used to drive the business
• Experience in technical leadership or mentorship
• Strong communication and collaboration skills
• Any schedule requirements (ie East coast time) to maximize overlap with team members in India
• Proven ability to solve complex problems in a dynamic and evolving environment

Desirable

• We are seeking a Senior Analytics Engineer to create clean, curated, and organized data sets used across Arcadia
• The role will be hands-on and collaborative, building data assets that enable analysis and drive daily business decisions
• You’ll bring an engineer’s rigor and a seasoned data modeler’s expertise to our thorniest data modeling problems, helping to lead our efforts to organize, rationalize, and produce enriched data products on our data
• Our data lake is hosted on Snowflake and that’s also where we are building our curated data layer–we call it the Unified Data Model–and produce analytics pipelines for our derived data products–our Solutions business
• You’ll work primarily with SQL in dbt; we use dbt Core, orchestrated in Argo and, in some instances, Prefect
• This is an excellent opportunity for someone who relishes the chance to engage with cutting-edge technology, influence the development of a world-class data ecosystem, and work in a fast-paced environment on a high-performing team
• As the senior-most individual contributor on our Data and Analytics Engineering team, you’ll work with our Director of Data and Analytics Engineering to define and drive our data strategy and best practices
• Transform, test, deploy, and document data to deliver clean and trustworthy data for analysis to end-users
• Collaborate with subject matter experts, engineers, and product managers to identify the most elegant and effective data structures to understand our constantly growing and evolving business
• Help bring engineering best practices (reliability, modularity, test coverage, documentation) to our DAG and to our Data team generally
• Collaborate with data engineers to build robust, tested, scalable ELT pipelines
• On a daily basis, this role will perform:
• Data modeling: model raw data into clean, tested, and reusable datasets to represent our key business data concepts. Define the rules and requirements for the formats and attributes of data
• Data transformation: build our data lakehouse by transforming raw data into meaningful, useful data elements through joining, filtering, and aggregating source dataData documentation: create and maintain data documentation including data definitions and understandable data descriptions to enable broad-scale understanding of the use of data
• Employ software engineering best practices to write code and coach analysts and data scientists to do the same