Jobber · 14 hours ago
Senior Software Engineer–Data & ML Platform
United States
Full-time
Remote
Senior Level
CA$126K/yr - CA$170K/yrJobber is a company dedicated to helping small businesses succeed through technology. They are seeking a Senior Software Engineer to join their Data & ML Platform team, where the role involves building scalable platforms and improving data systems to support analytics and machine learning initiatives across the organization.
MobileSaaSSmall and Medium BusinessesTask Management
Responsibilities
Build scalable platforms, frameworks, and self-service tooling that enable engineers, analysts, and data scientists to work effectively with data and machine learning. Partner closely with Product, Engineering, and ML teams to understand their needs and translate them into intuitive, well-documented capabilities that improve developer experience and reduce friction
Design, operate, and evolve core platform systems—including compute platforms, job orchestration engines, CI/CD workflows, and production ML infrastructure—with a focus on performance, scalability, and cost efficiency. Continuously improve automation and operational practices to reduce toil and enable teams to move faster with confidence
Apply strong software engineering fundamentals to build new platform capabilities that unlock faster experimentation, safer deployments, and more scalable data and ML use cases. Contribute to long-term technical direction by identifying gaps, proposing improvements, and evolving the platform to support Jobber’s growth and future ambitions
Collaborate with upstream and downstream teams to ensure high-quality data flows through the platform, including reliable ingestion, schema enforcement, and foundational transformations. Establish standards and guardrails that promote data integrity, consistency, and trust while enabling teams to build on top of the platform without duplicating effort
Team members participate in a one-week on-call rotation to support the reliability of our data and ML platforms that may include off business hours support. Incidents outside regular working hours are compensated with time off in lieu to support a healthy balance. Occasionally, planned maintenance or major changes may require weekend on-call coverage, with a strong focus on preparation and minimizing disruption
Qualification
Required
Designing and building scalable, reliable distributed systems in a cloud environment (AWS or equivalent)
Strong understanding of system design trade-offs, including scalability, fault tolerance, performance optimization, and cost efficiency
Strong proficiency in backend development using Python, with experience building production-grade services and APIs
Experience designing and maintaining APIs and internal services that support data workflows; Ability to write clean, maintainable, and well-tested code that supports long-lived platform capabilities
Solid experience working with SQL and large-scale data processing systems, including data warehouses and lakehouse-style platforms
Hands-on experience with data transformation and analytics tooling—not limited to dbt, Pandas, Polars, or similar frameworks used for data modeling, transformation, and analysis
Experience building and operating data pipelines, including CDC systems (e.g., AWS DMS or similar) and batch or streaming workflows
Familiarity with data quality practices such as schema enforcement, deduplication, and anomaly detection
Experience building and maintaining CI/CD pipelines to test, deploy, and operate backend, data, and platform systems
Familiarity with containerization and deployment workflows using tools such as Docker and cloud-native services
Strong operational mindset, including monitoring, alerting, incident response, and continuous improvement of developer workflows
Strong communication skills with the ability to work effectively across Product, Engineering, and ML teams
Experience partnering with stakeholders to translate requirements into well-designed technical solutions
Ability to document systems, share best practices, and contribute to a culture of operational excellence and continuous learning
Preferred
Experience designing or evolving data and platform systems such as lakehouse architectures, data warehouses, and orchestration platforms (e.g., Iceberg-based lakehouses, Redshift, Snowflake, Airflow, AWS Glue)
Familiarity with ML workflows and model deployment patterns, but deep ML expertise is not required
Experience with streaming platforms (Kafka, Kinesis) or emerging data technologies such as vector databases
Benefits
Equity rewards
Annual stipends for health and wellness
Retirement savings matching
Extended health package with fully paid premiums for body and mind
Dedicated Talent Development team
Access to coaching, learning, and leadership programs
Company
Jobber
Jobber is cloud software that helps mobile service businesses organize their scheduling, invoicing, CRM, and team management.
Founded in 2011
501-1000 employees
H1B Sponsorship
Jobber has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2024 (1)
Funding
Current Stage
Late StageTotal Funding
$183.46MKey Investors
General AtlanticSummit PartnersOMERS Ventures
2023-02-07Series D· $100M
2021-01-12Series C· $59.81M
2018-01-01Series B· $16M
Leadership Team
Sam Pillar
Founder & CEO
Forrest Zeisler
Co-Founder and CTO
Recent News
2025-12-15
Tech Funding News
2025-11-05
Company data provided by crunchbase