Data Engineer

Opportunity

UJET 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 Do

Data 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

Compensation

Annual 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.

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