Mid-Senior Data Engineer – SQL, Python, dbt & Snowflake

Motion Recruitment; California; On-site; USD 120,000 - 180,000; Full time

Job summary

Motion Recruitment Partners LLC is seeking a Mid-Senior Data Engineer to design and maintain production data pipelines and data models in a City of Industry, CA environment. The role emphasizes hands-on development and ownership of data operations.

You will work with SQL, Python, dbt, and cloud tech to support reporting, analytics, and operational use cases across internal and third-party data sources. The team values reliability, scalability, and collaboration with engineering and product teams.

Qualifications

• Strong SQL skills, including complex joins, window functions, aggregations, NULL handling, and data grain.
• Hands-on Python development in production.
• Professional experience building or supporting production data pipelines.
• Experience with a modern data transformation framework; dbt strongly preferred.
• Strong understanding of dimensional data modeling, including: Fact and dimension tables, Data grain, Conformed dimensions, Slowly changing dimensions.
• Experience supporting production environments, including deployments, monitoring, environment management, troubleshooting, and incident response.
• Strong experience with Git, pull requests, code reviews, and CI/CD.
• Ability to independently investigate and debug unfamiliar technical problems.
• Strong communication skills and ability to work across technical and business teams.
• Comfortable contributing within an established architecture and engineering environment.

Responsibilities

• Design, build, and maintain production-grade data pipelines and transformations
• Develop and maintain reliable data models supporting reporting, analytics, and business applications
• Work extensively with SQL, Python, dbt, and cloud-based data technologies
• Own day-to-day production data operations, including orchestration, scheduled refreshes, monitoring, and alerting
• Troubleshoot pipeline failures, data quality issues, and other production incidents
• Support database administration activities, including user access, roles, permissions, performance, and maintenance
• Manage data deployments and contribute to CI/CD and infrastructure automation
• Investigate unfamiliar or poorly documented data sources and determine how systems, schemas, and integrations function
• Build data solutions supporting reporting, billing, customer, and operational use cases
• Integrate and work with data from internal, third-party, and legacy systems
• Partner with engineering, product, operations, and business teams to translate requirements into technical solutions
• Participate in code reviews and contribute to engineering standards and best practices
• Improve documentation, knowledge sharing, and overall platform reliability

Skills

SQL

Python

dbt

Data pipelines

Git & CI/CD

Tools

Snowflake

Azure

Azure Data Factory

ADLS Gen2

Key Vault

Terraform

Job description

Mid-Senior Data Engineer – SQL, Python,dbt& Snowflake

City of Industry, CA | Full-Time

Our client is a growing organization seeking aData Engineerto join its expanding technology team. This is a hands‑on role focused on building and maintaining production data solutions, supporting critical data operations, and improving the reliability and scalability of the overall data environment.

The ideal candidate is a strong hands‑on engineer who enjoys working with production systems, troubleshooting unfamiliar problems, and taking ownership of data pipelines and operational processes.

What You’ll Be Doing

• Design, build, and maintainproduction-grade data pipelines and transformations

• Develop and maintain reliabledata modelssupporting reporting, analytics, and business applications

• Work extensively withSQL, Python,dbt, and cloud-based data technologies

• Own day-to-day production data operations, includingorchestration, scheduled refreshes, monitoring, and alerting

• Troubleshoot pipeline failures, data quality issues, and other production incidents

• Support database administration activities, includinguser access, roles, permissions, performance, and maintenance

• Manage data deployments and contribute toCI/CD and infrastructure automation

• Investigate unfamiliar or poorly documented data sources and determine how systems, schemas, and integrations function

• Build data solutions supportingreporting, billing, customer, and operational use cases

• Integrate and work with data from internal, third-party, and legacy systems

• Partner with engineering, product, operations, and business teams to translate requirements into technical solutions

• Participate incode reviewsand contribute to engineering standards and best practices

• Improve documentation, knowledge sharing, and overall platform reliability

Required Qualifications

• StrongSQLskills, including complex joins, window functions, aggregations, NULL handling, and understanding of data grain

• Hands-onPythondevelopment experience, including maintaining code running in production

• Professional experience building or supportingproduction data pipelines

• Experience with a modern data transformation framework;dbtstrongly preferred

• Strong understanding ofdimensional data modeling, including:

  • Fact and dimension tables

  • Data grain

  • Conformed dimensions

  • Slowly changing dimensions

• Experience supportingproduction environments, including deployments, monitoring, environment management, troubleshooting, and incident response

• Strong experience withGit, pull requests, code reviews, and CI/CD

• Ability to independently investigate and debug unfamiliar technical problems

• Strong communication skills and ability to work across technical and business teams

• Comfortable contributing within an established architecture and engineering environment

Preferred Qualifications

• Experience withSnowflake

• Experience withMicrosoft Azure

• Familiarity withAzure Data Factory (ADF), ADLS Gen2, and/or Key Vault

• Terraformor other Infrastructure-as-Code experience

• Experience working withmulti-tenant or customer-facing data

• Experience integrating with or reverse-engineeringlegacy and third-party systems

• Familiarity with BI, analytics, and downstream data consumption patterns

• Experience working withsupply chain, transportation, warehousing, logistics, or other operational data

AI & Modern Engineering

The engineering team incorporatesAI-assisted toolsinto its development and problem-solving workflows. Candidates should be comfortable using AI tools thoughtfully to:

• Investigate unfamiliar codebases, schemas, documentation, and systems

• Research and evaluate potential technical approaches

• Automate repetitive engineering tasks and workflows

• Improve development and troubleshooting efficiency

• Build custom scripts, tools, agents, or other AI-assisted workflows

Candidates should also understand the limitations of AI-generated output and be able to explain how theyverify results, identify incorrect assumptions, and validate technical solutions before putting them into production.