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Lead Analytics Engineer

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The Lead Analytics Engineer will be responsible for spearheading the development and optimization of our data analytics frameworks and infrastructure. This role requires a deep understanding of DBT, Snowflake, and advanced SQL, along with expertise in ETL methodologies and orchestration tools such as Airflow and Dagster. The ideal candidate will also have a working knowledge of Python. As lead engineer, you will lead the development across one of 3 organization pillars (finance, ops or revenue).  You will partner closely with the leads of each pillar to drive consistency and reusability of warehouse objects.

Key Responsibilities:

  • Leadership and Mentorship:
    • Mentor members of the analytics engineering team, providing technical guidance, and support on code and projects.
    • Foster a collaborative and innovative team environment, encouraging professional growth and development.
  • Strategic Planning:
    • Define and execute the analytics engineering strategy, aligning with organizational goals and business needs.
    • Identify opportunities for process improvements and implement best practices in data analytics and engineering.
  • Project Management:
    • Oversee the design, development, and maintenance of scalable and efficient data models using DBT and Snowflake.
    • Manage multiple projects simultaneously, ensuring timely delivery and adherence to high-quality standards.
    • Collaborate with cross-functional teams to gather requirements and deliver data-driven solutions and insights.
  • Technical Implementation:
    • Develop and optimize SQL queries and scripts for data transformation and aggregation.
    • Implement and manage ETL processes, ensuring data accuracy and integrity.
    • Lead the design and implementation of data orchestration workflows using tools such as Dagster or Airflow.
    • Build out automated AI workflows using LLMs like ChatGPT, integrating advanced AI capabilities into data processes.
    • Ensure compliance with data governance and security policies.
  • Collaboration and Communication:
    • Work closely with data scientists, analysts, and other stakeholders to support data modeling and analysis efforts.
    • Communicate effectively with technical and non-technical stakeholders, translating complex technical concepts into actionable insights.
  • Continuous Improvement:
    • Champion the use of GIT for version control and collaborative development.
    • Promote a culture of continuous learning and improvement within the analytics engineering team.

Qualifications:

  • 3-5 years of proven experience as a Lead Analytics Engineer or similar role, with a strong portfolio of successful data projects.
  • Expert knowledge of SQL and database management systems, particularly Snowflake.
  • Extensive experience with ETL methodologies and data modeling.
  • Proficient in orchestration tools like Airflow and Dagster.
  • Hands-on experience with GIT for version control.
  • Programming skills in Python and familiarity with data pipeline development are highly desirable.
  • Excellent problem-solving skills and the ability to work independently or as part of a team.
  • Strong communication skills, both verbal and written.

Education:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
  • Advanced degrees or professional certifications related to data engineering are preferred.

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