Analytics Engineer Job at Atlan

Atlan is hiring for the role of Analytics Engineer!

Responsibilities of the Candidate:

• Design, build, and manage robust data transformation pipelines.
• Turn raw data into clean, reliable assets using SQL and modern data transformation tools (like dbt).
• Model data effectively within our Snowflake warehouse. You will ensure data quality through strong testing practices.
• Identify what tools to adopt and what to discard as the modern data stack evolves with AI.
• Collaborate closely with teams across Atlan, delivering the data needed to drive decisions and power our AI future.

Requirements:

• Expertise in Data Transformation & Modeling: You have strong hands-on experience designing, building, and maintaining reliable data transformation pipelines and scalable data models using expert SQL, modern transformation tools (like dbt), and cloud data warehouses (like Snowflake). Understanding modern data integration patterns (ETL/ELT tools like Fivetran) is key.
• Commitment to Data Quality & Reliability: Building trust in data is paramount. You ensure accuracy and reliability through rigorous testing, meticulous attention to detail, and collaborative development practices using tools like Git.
• Strong Problem-Solving Skills: You enjoy tackling complex data challenges, diagnosing issues, and translating ambiguous business needs into effective, practical technical solutions.
• Excellent Collaboration & Communication: You thrive working cross-functionally, building strong relationships, and explaining technical concepts clearly to diverse audiences, from engineers to business stakeholders.
• Deep Sense of Ownership: You take initiative and demonstrate end-to-end ownership of your work, feeling responsible for the quality, impact, and continuous improvement of the data assets you create.
• Passion for Enabling Insights: You're motivated by empowering others with data. Experience leveraging BI tools (especially Sigma) to visualize data and deliver actionable insights is highly valued.
• AI Ready: While you don’t need to be an AI expert, you need to be exploring the future of AI on analytics, data engineering and business intelligence and ready to make decisions that lay the groundwork for an AI centric data estate.