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Python Contract Job Jobs in Los Angeles, CA (NOW HIRING)

Staffingine LLC

Senior Data Scientist

Los Angeles, CA · On-site

Contract * Design develop and deploy machine learning models and algorithms using Python Lead data science projects from concept to implementation ensuring timely delivery and quality outcomes

Saransh Inc

Automation SDET

Newport Beach, CA · On-site

Contract Experience Required: 7+ Years Skill Metrics: Skills Required Python Yes Jenkins Yes Jmeter Yes Playwright Yes Top skills required for this role: * Playwright with Python or similar scripting ...

aKube

Senior Databricks Data Engineer - 1628

Calabasas, CA · On-site

$125 - $150/hr

Up to $130k to $150k PA depending on experience (no C2C or 1099 or sub-contract) Work Authorization: GC, USC Only Must Have: * Databricks * AI * Python * DevOps and CI/CD Responsibilities: * Design ...

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All JobsPython Contract Job JobsPython Contract Job Jobs in Los Angeles, CA

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How much do python contract job jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for python contract job in Los Angeles, CA is $63.17, according to ZipRecruiter salary data. Most workers in this role earn between $52.07 and $71.73 per hour, depending on experience, location, and employer.
Python Contract Job jobs near you
Infographic showing various Python Contract Job job openings in Los Angeles, CA as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $131,384 per year, or $63.2 per hour.

QA Lead Data Engineering - Long Term Contract

Pasadena, CA • On-site

Rootshell Enterprise Technologies, Inc.
11 - 50 employees
Learn more about Rootshell Enterprise Technologies, Inc.external

$140K/yr

Contractor

Re-posted 24 days ago

Job description

QA Lead - Data Engineering
Pasadena, CA
Long Term Contract
We are seeking a highly skilled QA Lead - Data Engineering to define and implement robust QA strategies, automated testing frameworks, and data quality assurance processes. The ideal candidate will have expertise in Google Cloud Platform (GCP), Databricks, ETL pipelines, SQL, Python scripting, and CI/CD workflows. This role requires a strong understanding of data governance, data validation, and test automation to ensure high-quality data engineering solutions.
QA Strategy and Leadership:
* Define and implement robust OA strategies, methodologies, and processes for data engineering projects.
* Lead and mentor a team of QA engineers, ensuring alignment with best practices and project goals.
* Collaborate with stakeholders to understand data quality requirements and translate them into test plans and case
Testing Frameworks and Automation:
* Develop and maintain automated testing frameworks for ETL pipelines, data lakes, and data ware holises on Google cloud platform, Databricks, and related services.
* Design data validation and verification processes to ensure the accuracy and consistency of data across pipelines.
* Automate regression, performance, and integration testing to minimize manual efforts.
Data Quality Assurance:
* Conduct root cause analysis for data quality issues and drive corrective actions.
* Ensure compliance with data governance policies and data security best practices.
* Develop data profiling and monitoring dashboards using tools like Google
* Monitor, Power BI, or custom solutions.
Technical Skills and Qualifications:
* GCP Expertise: Proficient in GCP, Dataflow, BigQuery, Cloud composer, and google Storage services.
* Databricks: Experience with Spark-based data engineering workflows, including Delta Lake.
* Testing Tools & Frameworks: Strong experience with tools like PyTest, dbt (data build tool), or similar testing frame works for data pipelines.
* SQL and Scripting: Advanced SQL skills for data validation with Python proficiency for automation.
* Big data Knowledge: Knowledge of Big Data processing and distributed computing. Understand the importance data modeling concepts
* CI/CD: Knowledge of CI/CD pipelines on or GitHub Actions, focusing on data engineering workflows.
* Data Governance: Familiarity with data governance tools and concepts such as metadata management, lineage, and data cataloging.
* Communication: Excellent communications skills, with the ability to synthesize, simplify and explain complex problems to different tunes of audience including executives

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