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Job Description & How to Apply Below
Overview
Jobber is seeking a Manager of Data Engineering for a 14‑month contract that may transition to a permanent role. Our Data Platform team builds and maintains the data infrastructure that powers the technology offered to small home‑service businesses.
The role
Reporting to the Director of Data, the Manager will lead a team of data engineers, partner with the Technical Program Manager on prioritization, and oversee technical decisions that span the Data and ML platforms.
Responsibilities
Live and breathe performance facilitation by helping your team master their craft while collaborating to build extraordinary experiences and systems.
Be committed to your people’s success by setting goals, holding regular 1‑on‑1s, providing constructive feedback, and mentoring team members to grow their careers.
Develop and scale a world‑class team by recruiting top talent, leveling up internal capabilities, and implementing processes that improve delivery and collaboration.
Own the strategy, roadmap, and delivery of high‑performance, scalable, and cost‑efficient data infrastructure including data stores, compute engines, and orchestration systems.
Ensure data systems are resilient, observable, and governed. Implement robust recovery strategies, proactive monitoring, and best practices for security, integrity, and compliance.
Partner across engineering, analytics, and go‑to‑market teams to deliver well‑structured, high‑quality product data and build tools, automation, and solutions that accelerate workflows and create impactful outcomes for Jobber’s small‑business customers.
Drive innovation and efficiency with the use of AI tools to support the data strategy. Enable the team to continuously explore, experiment, and improve the state of data tools with the help of AI.
Participate in a quarterly on‑call rotation, covering one week at a time. When an incident occurs outside of regular working hours, provide time off in lieu. Major maintenance work may require primary or secondary on‑call support over a weekend. The Manager role is required to be an incident responder when an incident occurs.
Qualifications
Proven experience managing engineering teams—ideally in data platform or software engineering—on a track record of delivering high‑quality software and data solutions.
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.
Experience implementing observability frameworks, SLAs, disaster recovery strategies, and other practices to ensure resilient, reliable, and compliant data systems.
The ability to lead and adapt in an agile environment, fostering a culture of continuous learning, critical thinking, and creative problem‑solving.
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.
Strategic thinking and roadmap planning capabilities, with experience shaping infrastructure initiatives that have measurable impact.
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.
Desired (but not deal breaker)
Hands‑on experience with modern data stack tools such as Redshift, Trino, dbt, Airflow, and Kafka; 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 architecture in a production environment.
Experience working with Engineering teams to influence upstream data design and instrumentation.
Exposure to data science and machine‑learning workflows and their infrastructure requirements.
Compensation
Minimum…
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