Senior Data Engineer

DataJobs; California (MO); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401k plan eligibility

Job summary

iDC Logistics, Inc. is seeking a Senior Data Engineer for an onsite role in City of Industry, CA. You will own the data platform from deployment to production, focusing on secure access, reliable transformations, and legacy reporting alignment.

You will work with SQL, Python, and dbt-style modeling, ensuring production pipelines are robust, auditable, and maintainable, while guiding teams on best practices and AI-assisted verification.

Qualifications

• Bachelor’s degree in a related field.
• 7+ years designing, developing, and maintaining large-scale data pipelines and data warehouses.
• Proficient SQL with complex joins, window functions, grain and aggregation tradeoffs.

Responsibilities

• Own environment setup, monitoring, and incident response for production data platform.
• Manage security-role hierarchies and grants, optimize performance and maintenance.
• Maintain pipeline automation and environment promotion for reliable releases.
• Build staging and production dbt models with defined semantics and tests.
• Validate new platform outputs against legacy reporting and billing figures.

Skills

SQL

Python

dbt

SQLMesh

Dataform

Git

Communication

Independent problem-solving

AI tooling

Production operations

Dimensional modeling

Education

Bachelor’s degree

Tools

Azure Data Factory

Azure ADLS Gen2

Azure Key Vault

AWS

GCP

Snowflake

Terraform

Databricks declarative pipelines

Job description

iDC Logistics, Inc. is hiring a Senior Data Engineer for an onsite role in the City of Industry, CA. This position focuses on taking a data platform into production with dependable operations, secure access control, and production-ready transformations, while also delivering scoped data work within established patterns.

You can expect a role that combines operational ownership (deployments, monitoring, incident response) with engineering depth (SQL, Python, dbt-style modeling, and production data pipeline reliability). If you enjoy building systems that other teams can depend on, and you’re comfortable validating outputs against legacy reporting and billing figures, this is a strong fit.

Responsibilities

• Own environment setup and management, including refresh and orchestration, monitoring and alerting, and incident response for a platform supporting production report delivery and billing.
• Manage security-role hierarchies and grants, along with performance and maintenance.
• Maintain pipeline automation and environment promotion so releases stay routine and reliable.
• Build staging and gold dbt models using defined business semantics and existing conventions, including tests.
• Flag requests that would conflict with established definitions to protect data consistency.
• Review teammates’ work, including AI-generated code, for correctness and adherence to standards.
• Analyze and absorb legacy and vendor source systems, and systems with undocumented schemas, as an ongoing part of the work.
• Validate that new platform outputs match legacy system reporting and billing figures before cutover.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or related field.
• 7+ years 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 reasoning about why a query returns what it returns.
• Production Python: experience writing and maintaining Python code that ran in production.
• Pipeline experience: ownership of scheduled production pipelines, including diagnosing and fixing failures.
• Transformation framework: working depth in at least one modern framework. dbt preferred; SQLMesh, Dataform, Coalesce, Databricks declarative pipelines, or a comparable in-house framework also qualify.
• Production operations: responsibility for running systems, including deployments, environment management, on-call or equivalent, and incident response.
• Dimensional modeling: grain, facts and dimensions, conformance, and slowly-changing history.
• Git-based workflow: branching, pull requests, code review, and CI.
• Communication: clear writing, conversation, and presentations, including explaining technical findings to non-technical stakeholders.
• Independent problem-solving: investigate unfamiliar problems substantially before escalating.
• AI tooling: uses AI tools routinely for research, design, and verification; builds tooling for personal 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

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
• Dental insurance
• Employee assistance program
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid time off
• Professional development assistance
• Referral program
• Vision insurance

Preferred Qualifications

• Multi-tenant or customer-facing data experience (isolation, audit, lineage)
• Azure (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: USD 140,000 - 180,000 per year.