Position Summary:

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:

• 4+ years of proven experience as a Lead Analytics Engineer, 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.
• Extensive data modeling experience
• 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.