Overview

Launched in 2017 in New York, N.Y., UPSTACK is transforming the infrastructure is sourced and sold. Through a powerful combination of the industry's leading advisors, advanced technology, and dedicated customer support resources—UPSTACK uses actionable business intelligence to architect and source customized technology solutions for businesses of all sizes. With UPSTACK, business buyers streamline IT procurement by tapping into a single source for mission-critical technology services from hundreds of proven providers, along with the professional guidance to identify and evaluate the best solutions.  

UPSTACK recently secured a substantial equity investment from Berkshire Partners, a firm with over 35 years of investment experience and deep sector expertise in technology and communications. The investment is being used to evolve UPSTACK's intuitive technology platform, expand its product and service portfolio and accelerate its direct investments in the industry's top-producing sales agencies. To date, the company has acquired over 34 independent agencies to become the largest and fastest-growing agency in the technology industry.

About the Team

At UPSTACK, the Engineering team is responsible for building software to help manage complex business processes and implementing complex system integrations. The Engineering team also works closely with the Product organization to develop and drive the long-term roadmap for our suite of software. 

Engineers at UPSTACK believe that clear is better than clever, sturdy is better than shiny, and done is better than perfect. We write testable, well-documented code that thoughtfully answers the needs of the company. We remember the human, whether that’s the user at the other end of the system or our fellow engineer. 

About the Role

The Manager, Data Engineering will provide technical and people leadership to the UPSTACK Data Engineering Team and will contribute to and help oversee the design, development, delivery, quality assurance, and maintenance of scalable data platform solutions, while collaborating closely with our data platform product owner and other stakeholders to ensure data is reliable, secure, accessible, and meets the needs of our end users. 

The manager will also focus on mentoring and developing team members, fostering a culture of continuous improvement while promoting collaboration and innovation within data engineering practices. Additionally, they will be responsible for managing performance, facilitating professional growth, and aligning team efforts with organizational goals to deliver high-quality data solutions.  

Critical Outcomes Expected

Reporting to the VP, Engineering, the Manager, Data Engineering will be responsible for supporting:

• Recruitment and Onboarding: Recruit, hire, and onboard new technical data roles, ensuring the team has the skills and diversity required to meet current and future tooling needs. 
• Coaching and Development: Offer coaching and feedback to support team members’ professional growth and development, focusing on enhancing data engineering skills, knowledge of new data technologies, and career progression.
• Team Management: Set clear team expectations, monitor progress, remove roadblocks, and support team members in achieving their goals in alignment with organizational goals.  
• Team Support: Understand team members’ needs, resolve conflicts, and build trust through empathy and active listening.  
• Team Support: Understand team members’ needs, resolve conflicts, and build trust through empathy and active listening. 
• Task Delegation: Delegate tasks, encourage autonomy, and create an overall positive environment that fosters innovation and confidence. 
• Product & Data Platform Roadmap Support: Contribute to product roadmap capability sizing and data platform roadmap prioritization and management, aligning data engineering initiatives with business goals and future data needs. 
• Product and Technology Development:  Assist in various areas of data product and technology development including backlog management, technology evaluation, technical decision-making (data solutions), data architecture design and implementation, and lifecycle management of data infrastructure and systems. 
• Collaboration with Product Owners: Partner with, and work alongside the data platform product owner within the agile process, ensuring alignment between data engineering, the product team, and other technical stakeholders to deliver high-quality data solutions. 
• Outsourcing and Contractor Management: Manage offshore/outsourcing relationships and contractor engagements as needed. 
• Data Reliability: Work closely with the data platform product owner and other stakeholders to ensure data is reliable, accessible, and meets the needs of our end users. 
• Data Strategy: Evaluate data engineering tools, processes, and business needs and implement self-service data platform strategy around data publication, security, organization, naming convention, shape, and change management policy. 
• Quality Assurance: Ensure thorough quality assurance practices are followed to deliver trusted data solutions. 
• Continuous Improvement: Foster a culture of continuous improvement within the team, promoting collaboration and innovation. 

Current Stack 

• Cloud Technologies 
  • AWS 
  • Lambda 
  • RDS 
• Data Storage 
  • Postgres 
  • Redis 
• Data Transformation & Analysis
  • Fivetran
  • Dataiku
  • dbt
  • Tableau 
• DevOps
  • DataDog
  • GitHub 
• Languages
  • Python
  • Ruby
  • JavaScript 
• Web Frameworks
  • Rails
  • React 
  • NestJS

Skills & Requirements

• Authorized to work in the U.S. and available to support East Coast business hours.
• 1-3 years of people management experience.
• 4-5 years of data engineering experience.
• Strong Technical Expertise: High proficiency in Python and SQL with solid experience in Postgres, Dataiku, dbt, and Fivetran (or similar relational database, ETL, and data science tools), enabling effective oversight of data pipeline development, ETL processes, and data warehousing solutions. 
• Data Engineering and Analytics: In-depth knowledge of data engineering principles, including data modeling, data integration, and analytics, ensuring robust data architecture that meets the needs of various stakeholders and supports real-time data-driven decision-making. 
• Agile Methodology Proficiency: Experience working in agile development environments, capable of guiding data engineering teams through agile processes, managing sprints, and ensuring timely delivery of scalable and reliable data solutions.
• Leadership and Mentoring: Proven ability to lead and mentor an engineering team, providing coaching and feedback to support professional growth, while fostering a collaborative and innovative team culture that emphasizes solution quality and continuous improvement. 
• Problem-Solving: Ability to help evaluate options and make informed technical recommendations in alignment with bigger-picture goals.  
• Collaborative and Supportive: Works well with others, actively contributing to team goals and supporting teammates. 
• Effective and Adaptable Communicator: Clearly explains technical concepts to all audiences, quickly adapts to new information, and evaluates trade-offs. 
• Confident, Humble, and Accountable: Demonstrates expertise with confidence and humility, taking full ownership and responsibility for work. 
• Critical and Self-Aware Thinker: Advocates for sound ideas, remains open to new perspectives, and identifies underlying assumptions. 
• Recruitment and Team Development: Successfully build and maintain a high-performing data team.   
• Technical Execution and Oversight: Successfully oversee and contribute to the technical execution of data integration and automation workflows using tools like Postgres, Fivetran, dbt, and Dataiku; ensuring that data pipelines are efficient, scalable, secure, easily maintainable and that solutions both adhere to best practices and architectural standards while meeting analytics and reporting needs. 

What Else We're Expecting

• History of operating successfully in a fast-paced, high-growth technology organization. 
• Exceptional core values – not only does the right thing, but does the thing right.  
• Excellent written and verbal communication skills. 
• Strong IT background; experience in network, voice, and data center implementations a plus. 
• High attention to detail. 
• Curious, resilient self-starter with a “can-do” attitude. 
• Not only adapts to but embraces change. 
• Collaborative with a willingness to roll up one's sleeves and work on projects and tasks. even if they fall outside of stated job responsibilities.   
• Solutions-oriented problem-solver that is focused on execution. 
• Entrepreneurial by nature. Not afraid to challenge the status quo in order to find better ways to get the job done. 
• Data fluent; leverages empirical evidence to inform decisions and opinions. 
• Demonstrated ability to work across multiple time zones and cultures.