Manager, Data Engineering

As a Manager, Data Engineering you are responsible for leading and managing a team of Data Engineers while actively contributing to the development and implementation of data engineering solutions. Your primary focus will be to address pain points related to engineering culture, provide coaching and feedback to your direct reports, and stay 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 engineering processes. This role requires 50–60% hands-on coding in addition to leadership and strategic responsibilities 

Team Leadership: You are responsible for a diverse team of data engineers, at different levels in their careers. You will foster their growth and well-being of the team and pair with them to solve interesting engineering challenges. You will work closely with data solutions managers and your director to ensure adequate and sustainable data engineering coverage across engagements.  

• Leads a team of data engineers, typically consisting of 5 to 8 direct reports.  
• Advocates for and protects team time to contribute to internal projects.  
• Pushes for sustainable technical architectural decisions in the team with a long-term approach in mind.  
• Recruit, train, supervise and support the development of team members in data engineering functions.  
• Conduct performance reviews under the guidance and in close collaboration with the functional associate director / director.  

Functional Leadership: You are responsible for working with clients to build guidelines for the infrastructure to support the storing and movement of data and implement data engineering tools to support data-driven decision-making and develop strategies to ensure consistency and security with their data products.  

• Has a good balance of technical knowledge and can coach other engineers and data solutions managers on their areas of expertise.  
• Supports engineering projects on tier 1 client engagements with assistance from more senior Engineering management, translating client business questions and needs into engineering requirements.  
• Advises clients on selection of data engineering tools, systems, and approaches.  
• Selects, configures and implements engineering solutions and tools using best practices.   
• Contributes advanced engineering skills and knowledge to client engagements.  
• Contributes to internal and externally facing resources for data engineering teams (e.g. add to internal wiki, write a blog post, etc.)  
• Plans for sustainable growth of their team and builds a clear roadmap for milestones and impact; leads hiring for their team based on hiring plans provided by People Ops and Director. 

Project Delivery: You are responsible for improving core data engineering deliverables by supporting internal process reviews, recommending, and implementing data engineering tools and technologies that best suit the client’s needs.  

• Directly supports day-to-day execution of work, while may need support in driving larger, strategic pieces.   
• Is accountable within their team for the availability and reliability of the systems their team builds.  
• Makes sure the team is prioritizing availability and quality vs. new feature development appropriately.  
• Work collaboratively with other data functional teams such as data analytics, analytics engineering, and data solutions to achieve client goals.  
• Guide a team in the successful and timely execution of project deliverables.  
  • Be accountable for the quality of your team’s work

• Intermediate / expert proficiency with cloud data warehouses (e.g., Snowflake, Databricks, Azure)  
• Intermediate / expert proficiency with common data integration / orchestration platforms (e.g., concepts like CDC, ELT and tools such as Fivetran, DLT, 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.  
• Strong analytical and problem-solving skills.  
• Excellent communication and collaboration skills.