Senior Data Engineer

Senior Data Engineer will help bring a production data platform to steady operations while delivering scoped production transformations and platform improvements.

Responsibilities

• Own production operations for a platform supporting production reporting delivery and billing
• Manage environment setup and management, including refresh and orchestration operations
• Run monitoring and alerting and handle incident response
• Maintain security-role hierarchies and grants; support performance and ongoing maintenance
• Build and maintain pipeline automation and environment promotion so deployments are routine and reliable
• Create staging and gold dbt models with tests aligned to defined business semantics and existing conventions
• Identify and flag requests that would conflict with established definitions
• Review teammates’ work, including AI-generated code, for correctness and adherence to standards
• Analyze and absorb legacy and vendor source systems, including working with many undocumented schemas as an ongoing requirement
• Validate new platform outputs against legacy system reporting and billing figures prior to cutover
• Deliver well-scoped production data work (for example dbt modeling and transformation) within existing patterns to support parallel architecture and design work

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or related field
• 7+ years of experience designing, developing, and maintaining large-scale data pipelines and data warehouse solutions
• SQL at working depth, including joins, window functions, grain and aggregation tradeoffs, NULL semantics, and query reasoning
• Production Python experience, including writing and maintaining Python code that ran in production
• Production pipeline ownership, including scheduled pipelines and diagnosing and fixing failures
• Transformation framework experience: strong working depth in at least one modern framework (dbt preferred; SQLMesh, Dataform, Coalesce, Databricks declarative pipelines, or comparable in-house framework also qualify)
• Production operations experience, including deployments, environment management, on-call (or equivalent), and incident response
• Dimensional modeling knowledge: grain, facts and dimensions, conformance, and slowly-changing history
• Git-based workflow: branching, pull requests, code review, and CI as standard practice
• Clear communication in writing, in conversation, and in presentations, including explaining technical findings to non-technical stakeholders
• Independent investigation of unfamiliar problems prior to escalation
• AI tooling used as a regular part of engineering work for research, design, and verification; built tooling for their own workflow; verifies AI output before relying on it

Technologies

• SQL, Python, dbt
• SQLMesh, Dataform, Coalesce, Databricks declarative pipelines
• Git
• Azure (Data Factory), Azure (ADLS Gen2), Azure (Key Vault)
• AWS, GCP
• Snowflake
• Terraform

Preferred Qualifications

• Multi-tenant or customer-facing data experience (isolation, audit, lineage)
• Azure experience (Data Factory, ADLS Gen2, Key Vault); AWS or GCP experience transfers
• Snowflake
• Terraform or equivalent infrastructure-as-code
• Legacy and vendor-system reverse-engineering
• Logistics, supply-chain, or warehousing domain experience
• Familiarity with BI tools

Compensation and Location

• Location: City of Industry, CA (onsite)
• Salary: USD 140,000 - 180,000 per year

Benefits

• Medical, dental, and vision insurance
• Basic and voluntary life and voluntary ancillary coverages for accident, critical illness and hospital indemnity
• Paid sick leave
• Bereavement pay
• Holiday and vacation pay
• 401k plan eligibility on the first day of the third month following hire date
• 401(k)
• 401(k) matching
• Employee assistance program
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Professional development assistance
• Referral program