Analytics Engineer

Summary

Join Ordergroove's growing data team as a pioneering Analytics Engineer, playing a critical role in defining analytics engineering. You will design and optimize data models, build robust data pipelines, and ensure high-quality data for stakeholders. This foundational role offers the freedom to establish best practices and influence the direction of analytics across the organization. Leverage your skills in SQL, dbt, and Python in a collaborative, fast-paced environment. You will collaborate with engineers, product managers, and business stakeholders to define key business metrics and ensure seamless data access. Success involves enabling self-service analytics through clear documentation and ensuring data quality and reliability.

Requirements

• Experience: 3+ years in a data role (Analytics Engineer, Data Engineer, or Full Stack Data Scientist) in a data driven organization
• Advanced SQL & Data Modeling: Strong experience in designing, building, and optimizing SQL-based data models, with an understanding of normalization trade-offs
• Data Pipeline Development: Hands-on experience with dbt and modern ETL/ELT frameworks, following best practices like version control and CI/CD
• Python & Data Engineering: Proficiency in Python for data transformations, workflow orchestration (Airflow), and automation
• Data Warehouse Design: Experience designing and optimizing a data warehouse in BigQuery, including structuring datasets, partitioning, clustering, and optimizations to manage performance at scale
• Data Quality & Governance: Experience implementing monitoring systems, ensuring data consistency, and maintaining high-quality data
• Strong Communicator: Able to translate technical concepts for non-technical stakeholders, collaborate with engineers, and present insights effectively
• Proactive & Self-Driven: Comfortable working alone, driving projects, and building relationships across teams
• Impact-Oriented: Focused on delivering high-value solutions that empower stakeholders and improve business outcomes

Responsibilities

• Design, develop, and maintain core data models in dbt and SQL, ensuring consistency, accuracy, performance, and appropriate levels of normalization to meet business and technical needs
• Build and maintain data pipelines to ingest, transform, and serve data efficiently, leveraging tools like dbt and Airflow
• Collaborate with engineers, product managers, business stake holders to define key business metrics and ensure seamless data access
• Enable self-service analytics by creating clear documentation and supporting teams in using data effectively
• Ensure data quality and reliability by implementing monitoring systems and designing processes that maintain long-term data integrity
• Drive efficiency and cost effectiveness by building performant models that optimize cloud data usage

Preferred Qualifications

• Interest in Data Science and Machine Learning, while this is not a pure data science role, familiarity with ML concepts and their applications in analytics will be a plus
• Knowledge of statistical analysis and experience applying it in real-world data problems
• Familiarity with Django or API, which can be valuable when building internal data tools or collaborating closely with backend engineering teams on data-related features

Benefits

• Flexible PTO
• Totally remote (anywhere in the US) workforce
• An annual personal development budget that you use for what matters to you (wellness, career development, productivity at home, etc)
• Competitive compensation (including stock options)
• Incredible, affordable benefits