Senior Data Engineer, Jobber

• We are seeking a highly skilled Senior Data Engineer with a strong focus in data modelling, data engineering practices and data standards to play a key role in the development and evolution of our Data Integration Platform
• Excellent ETL pipeline development skills and hands on experience with Orchestration (Airflow)
• Experience with CI/CD practices and optimizing data flow within high-volume, scalable infrastructures
• Experience with Data ingestion systems (Fivetran/Airbyte) and Reverse ETL systems (HighTouch/Census)
• Experience with dimensional modeling, star schemas and warehousing concepts
• Experience with message queues (Kafka), real-time stream processing and lambda architecture
• Proficiency in designing, developing, and maintaining efficient batch and real-time data pipelines within a cloud infrastructure (preferably AWS)
• Strong skills in SQL, stream processing, Containerization (ECS orchestration) and AWS Lambda to create reliable and scalable data solutions
• Expertise in developing scripts, serverless applications, and automated workflows to ensure data integrity and accessibility
• Ability to explain complex data concepts to both technical and non-technical stakeholders
• You can work independently, collaborating with cross-functional teams and stakeholders to meet data needs and contribute to data-driven decision-making

Desirable

• We’re looking for a Senior Data Engineer to be part of our Data Integration team
• The Data Integration team is a part of the Data org and is responsible for the ingress and egress of data critical to analytics, reporting and GTM decision-making at Jobber
• The team is responsible for managing various tools, systems and services whose core function is to move batch and event-based data between different internal and external systems
• The team is also involved in developing capabilities that will increase the speed to delivery, improve quality of data and enable self-serve for stakeholders
• This is an opportunity to play a pivotal role in the evolution of our data integration platform, driving forward-thinking solutions that are fundamental to increasing the scalability, resiliency and quality of our Data systems
• You will work in an environment that values both technical expertise and leadership, where your contributions will have a significant impact on the team and the broader organization
• Join us, and be a part of this innovative team, strategic in its approach in solving complex and impactful challenges!
• The ideal candidate will manage data ingress systems, manage pipelines that transform data, build models to improve ease of integration with external CRM systems and build tools to automate components of data ingress/egress
• The data engineer will work closely with the Data Platform team to establish Data contracts for data in the raw layer, implement data quality practices and collaborate with GTM teams to move data to external systems for time critical use-cases
• This role is crucial to enabling seamless integration of data between Jobber and external systems
• At Jobber we never stop growing and learning, and you shouldn’t either. Through continuous 1:1s, dedicated feedback and support from your manager and our Talent Development team, and your own sense of curiosity, we hope you develop to another level with your skill set
• Develop tools, frameworks, and workflows that reduce manual processes, enhance data accessibility, and enable data-driven decision-making
• Build robust alerting and monitoring systems to maintain data quality and reliability
• Collaborate across functions to support experiments and analyses that drive impactful business decisions
• Day-to-day experience working closely with software engineering teams, fostering a collaborative environment for data-driven development
• Work closely with data platform engineers, data scientists and product teams to sync data between Jobber and external systems
• Use tools like Airflow and dbt to streamline ETL/ELT workflows, ensuring seamless data flow and integration
• Build data models that enable easier integration and self-serve in the Data Integration Platform
• Lead initiatives to research and propose emerging technologies, strengthening our data stack with a focus on performance, scalability, and maintainability
• Participate in design and code reviews, actively contributing to knowledge sharing and mentoring within the team
• Take ownership of data quality, establishing best practices to maintain high trust in data across the organization