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Articulate is looking for a Sr. Analytics Engineer to join our amazing Data team! As a Senior Analytics Engineer, you'll transform the data landing in our data warehouse into self-serve data artifacts. The goal of this role is to help our cross-functional data consumers find the right data set for their analysis and answer their questions quickly through a self-service data platform. While the role is primarily responsible for building the data foundation for reporting and analysis, it is expected to provide necessary support in building and improving Articulate’s data literacy and infrastructure.
Job Responsibility:
Provide flexible, trustworthy data models by transforming data from multiple sources with DBT, testing for quality, deploying to visualization tools such as Looker or Tableau, and publishing documentation
Collaborate directly with stakeholders to define problems and determine requirements for a solution
Set and maintain best practices for data models and processes, including project architecture and QA
Proactively identify gaps or design flaws in our data models, and bring recommendations for how to fix them
Own documentation of our tools and data, both for our team and for external users
Lead discovery on data tools and infrastructure, including setting goals for tooling, continuous analysis of existing tooling, and exploring new tools and features we may adopt
Participate as a technical leader in project planning, helping to create well-defined tasks to address data initiatives
Mentor more junior members of the data team
Represent the data team in some technical architecture and planning conversations
Identify and share data risks and dependencies in these contexts
Make recommendations for data collection and upstream data structure to support downstream data quality
Support a culture of data-driven decision-making across the organization
Requirements:
8+ years of experience in data or analytics roles
At least 5 years in analytics engineering, preferably within a fast-paced tech company or data-driven organization
Expert in end-to-end data workflows, from data collection to analysis and presentation, with most expertise in data modeling
Confident in translating raw data to reusable, business-friendly data models
Proven experience owning and leading the creation of reliable, flexible data models in an enterprise data warehouse
Expertise in SQL (writing and analyzing complex queries)
Expertise in Data Build Tool (dbt)
Expertise in Looker/Tableau (defining data models and measures)
Experience building semantic layers using dbt, Looker, or Snowflake’s semantic tables
Ability to write complex SQL, run ad-hoc data discovery, and build data models
Experience optimizing queries and models for performance and cost
Proficiency with orchestration tools like Airflow, Prefect or Dagster
Proficiency with ETL tools like Fivetran or Stitch
Comfortable breaking down large projects into smaller components, delegating tasks to more junior team members and creating clear, well-defined tasks
Excellent communication skills
Ability to translate complex business questions into easy-to-use data models
Nice to have:
Experience with event-based models or product telemetry for SaaS product usage analysis
Experience in Agile or Kanban workflow
Experience with Salesforce (or similar Enterprise CRMs), Marketo
Basic understanding of data security and compliance requirements
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