OpportunityUJET is looking for a Data Engineer to join our growing Data Platform team. You'll own our data systems end to end: CDC replication out of production MySQL, the pipelines and jobs that shape data in BigQuery, the Terraform-managed infrastructure underneath, and the Looker models on top. dbt is central to how we work. You'll build models yourself and set the patterns that let analysts, product partners, and engineers ship their own safely. You should be comfortable debugging a replication issue in the morning and tuning a Looker explore in the afternoon.
This data powers reporting for thousands of customer tenants, including embedded Looker analytics for enterprise customers, and the internal metrics our Operations and Finance teams run the business on. Over the coming year, our focus is data trust and reliability, platform modernization, and treating data as a product. You'll help shape all three.
Our Stack- Sources and ingestion: Cloud SQL (MySQL) and BigQuery via GCP Datastream (CDC)
- Warehouse and transformation: BigQuery, dbt (dbt Labs)
- Orchestration: GKE-based, using Kubernetes CronJobs and Argo Workflows
- Semantic layer and reporting: Looker / LookML
- Languages: Python and SQL; core application infra is Ruby on Rails and Go
What You'll DoData platform enablement- Build and evolve the data platform foundations that make it easy and safe for others to ship dbt work (project structure, environments, permissions, patterns, documentation)
- Establish and maintain standards and guardrails for dbt development (testing strategy, source freshness, documentation, code review practices)
- Improve the developer experience for data workflows, including CI/CD, automated checks, and repeatable deployment patterns
- Manage data infrastructure as code with Terraform, including pipelines, IAM, and environments
Ingestion and CDC- Improve and troubleshoot CDC replication from MySQL to BigQuery with Datastream
- Build tooling for backfills, drift detection, and reconciliation between source databases and the warehouse
- Contribute to infrastructure decisions on data ingestion and platform evolution, including latency, throughput, and alternative CDC approaches
Trusted metrics and analytics- Partner with Analytics and Finance to define and deliver trusted metrics and dashboards in Looker
- Build and maintain analytics-ready datasets that support self-serve reporting and experimentation
- Support customer-facing, multi-tenant reporting with a focus on correctness, tenant isolation, and query performance
Data modeling and transformation (dbt + BigQuery)- Develop and optimize BigQuery data models for analytics and product use cases
- Implement ELT best practices in dbt, including testing, documentation, and versioning
Pipelines, reliability, and cost- Design, build, and maintain scalable data pipelines using Python, dbt, and containerized jobs on GKE
- Ensure data quality, reliability, and observability for critical datasets and reporting
- Optimize performance and cost across BigQuery and data pipelines
Cross-functional delivery- Integrate data workflows with backend services and APIs
- Work with Product and Engineering to translate business needs into data solutions
Requirements- 5+ years of software engineering experience, with deep data platform experience
- Strong programming skills in Python
- Strong SQL skills and experience with analytical data modeling
- Hands-on experience with BigQuery (or a similar cloud data warehouse)
- Production experience with dbt (dbt Labs), including building models yourself
- Experience building or improving the infrastructure around data workflows (reliability, observability, CI/CD, permissions, environments, deployment patterns)
- Experience with infrastructure as code, preferably Terraform
- Experience with a major cloud platform (GCP preferred)
- Strong software engineering fundamentals (testing, version control, code reviews)
Preferred Qualifications- Experience with GCP services (Datastream, Cloud Storage, Cloud Run, and Pub/Sub)
- Change data capture experience (GCP Datastream or MySQL binlog/GTID replication)
- Experience with Kubernetes-based orchestration (Argo Workflows or similar)
- Experience with Looker (LookML, semantic modeling, dashboards)
- Familiarity with Ruby on Rails or Go, which power the application-layer services our data platform depends on
- Experience collaborating with Product to gather requirements and translate business needs into data solutions
CompensationAnnual US Hiring Range: $140,000 - $160,000*
*A candidate's actual placement within this range will depend on geographic location, work experience, education, and/or skill level.
#LI-Remote
Why UJET?- Impactful Work: Be at the forefront of innovation, directly shaping the future of customer experience.
- Dynamic Culture: Join a collaborative, inclusive team that values big ideas, creative solutions, and powerful relationships.
- Comprehensive Benefits: Medical, dental, vision, 401(k) plan, wellness benefits, and more.
