Manager of Data Engineering

Join Jobber as the Manager of Data Engineering, where you will lead a team of data engineers and collaborate with cross-functional teams to deliver high-quality product data and innovative solutions. You will be responsible for managing team performance, shaping technical decisions, and owning the strategy and delivery of data infrastructure. This role requires strong leadership, technical expertise, and a commitment to continuous learning and improvement.

• Lead and manage a team of data engineers, overseeing their performance, supporting individual growth, and ensuring high-quality deliverables.
• Own the strategy, roadmap, and delivery of high-performance, scalable, and cost-efficient data infrastructure, including data stores, compute engines, and orchestration systems.
• Collaborate with cross-functional teams to deliver well-structured, high-quality product data and build tools, automation, and solutions that accelerate workflows.

• Excellent collaboration and communication skills, with the ability to work cross-functionally with engineering, product, analytics, and data science teams while mentoring and coaching direct reports
• The ability to lead and adapt in an agile environment, fostering a culture of continuous learning, critical thinking, and creative problem-solving
• Strategic thinking and roadmap planning capabilities, with experience shaping infrastructure initiatives that have measurable impact
• Experience implementing observability frameworks, SLAs, disaster recovery strategies, and other practices to ensure resilient, reliable, and compliant data systems
• A strong technical foundation in software and data engineering, including distributed data systems, orchestration frameworks, cloud infrastructure, performance tuning, scaling strategies, and cost optimization
• Hands-on experience in systems design, SQL, modern data tools, and data best practices, including modeling, governance, and quality management
• Strong leadership and mentorship skills, using your experience to guide, influence, and provide constructive feedback to direct reports—ensuring their growth and enabling the team to exceed its goals
• Proven experience managing engineering teams - ideally in data engineering domains- with a track record of delivering high-quality software and data solutions
• Hands-on experience with modern data stack tools such as Redshift, Trino, dbt, Airflow, Kafka, and familiarity with data processing frameworks such as Spark and Ray
• Background in building internal developer platforms, self-service data tooling, or workflow automation for data teams
• Sound understanding of lambda and/or kappa architecture, batch and streaming principles and experience implementing either of the two architectures in a production environment
• Experience in working with Engineering teams to influence upstream data design and instrumentation
• Exposure to data science and machine learning workflows and their infrastructure requirements