Analytics Engineering Manager

Location

Remote

As an Analytics Engineer Manager, you will be responsible for leading and managing a team of Analytics Engineers while actively contributing to the development and implementation of analytics engineering solutions. Your primary focus will be to address pain points related to analytics engineering culture, standardized development and modeling approaches, tools, and staying up-to-date with industry trends in a way that benefits the company. You will play a crucial role in driving employee retention, resourcing, learnings management, presales, feedback gathering, QA, and internal analytics engineering processes.

Responsibilities

Conducting regular one-on-one meetings with your team to identify and address career development opportunities, current project challenges, and guide individuals in
determining their next steps.
Collaborating with People Experience and Analytics Engineering leadership to strengthen and develop key skills, competencies, and expertise areas for your functional area, including planning recurring training and onboarding programs.
Improving the quality of client deliverables by supporting internal process reviews, building guidelines for data modeling and measuring and tracking deliverables to ensure client satisfaction.
Working closely with data solutions managers and your director to ensure adequate and sustainable analytics engineering coverage across clients‍

Responsibilities Breakdown
- Recruit, train, supervise and support the development of team members in the analytics engineering function
- Work collaboratively with other data functional teams such as data engineering, data analytics, and data solutions to achieve client goals
- Be accountable within their team for the accuracy, readability and scalability of the data models and solutions their team builds
- Guide a team in the successful and timely execution of project deliverables, while also supporting in driving larger, strategic initiatives
- Translate client business questions and needs into analytics and engineering requirements
- Advise clients on data modeling, ingestion and warehousing approaches
- Select, configure and implement analytics engineering solutions using best practices through tools like dbt, Snowflake, BigQuery and Fivetran
- Contribute to internal and externally facing resources for analytics engineering teams (e.g. add to internal wiki, write a blog post, etc.)

Skills & Qualifications

Technical Skills (Hard Skills)
- Expert proficiency with data transformation tools (e.g., dbt)
- Expert proficiency in data modeling approaches and philosophies (e.g., Kimball, OBT)
- Intermediate / expert proficiency with cloud data warehouses (e.g., Snowflake)
- Knowledge of common data integration patterns (e.g., CDC, ELT, etc.)
- Knowledge of common data integration / orchestration platforms (e.g., Fivetran, Azure Data Factory, Apache Airflow)
- Experience mentoring and advising other engineers
- Experience with optimizing resource allocation by assessing team members' strengths and assigning tasks according to their expertise, while promoting skill growth.

Essential Skills (Intangible Skills)
- Collaboration & Partnership: You can facilitate collaborative group activities and/or workshops with colleagues or external stakeholders in an agile capacity.
- Effective Communication: You reliably foster a culture of clear, concise, effective, audience-oriented communication for your team, other departments, and external stakeholders, ensuring those around you are actively listening as well as are understood.
- Developing Others: You understand your team's domain, share knowledge frequently with your teammates and contribute to the team's documentation. You proactively watch for opportunities to share knowledge and encourage others to do the same.
- Human Experience: You actively surface data relevant to the team, and design tests based on data-driven hypotheses. You look for data outside your immediate reach to further flesh out stakeholder needs. You ensure that every conversation you have with your team involves the needs of others, especially those who are not represented in the conversation.

Qualifications (Must Haves)

- You have managed and trained team members in analytics or engineering functions.
- You have experience in leading teams through organizational changes, mergers, acquisitions, or shifts in technology direction.
- Intermediate / expert proficiency with cloud data warehouses (e.g., Snowflake)
- Intermediate / expert proficiency with data modeling approaches and philosophies, and the tools that are used (e.g., dbt)
- Experience mentoring and advising other engineers
- Experience with optimizing resource allocation by assessing team members' strengths and assigning tasks according to their expertise, while promoting skill growth.

Compensation Range: $125,000 - $145,000 annually

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