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Sql Python Data Engineer Jobs in Los Angeles, CA

Harnham

Data Engineer

Irvine, CA · On-site

$175K/yr

... Data Engineering, or Analytics-focused roles ... Expert-level SQL and strong Python experience * Hands-on experience with dbt, Redshift, Looker ...

Dlapiper

Data Engineer

Los Angeles, CA · On-site

$123K - $148K/yr

Together. Summary The Data Engineer, Solutions & Data role designs, builds, and operates data ... Proficiency in SQL and Python. * Data pipeline tooling and cloud data services experience (Azure ...

Expleo

DATA ENGINEER

Los Angeles, CA · On-site

$123K - $148K/yr

Développement & Data Engineering - Développer des solutions de collecte, stockage et distribution ... Streamlit, dbt, SQL, Python, Power Query Réseau Bonne maîtrise des technologies suivantes

Expleo

DATA ENGINEER

Los Angeles, CA · On-site

$123K - $148K/yr

Developpement & Data Engineering - Developper des solutions de collecte, stockage et distribution ... dbt, SQL, Python, Power Query Qualifications Reseau Bonne maitrise des technologies suivantes

ALO

Lead Data Engineer

Beverly Hills, CA · On-site

$180K - $250K/yr

Data Engineering * dbt, SQL, Python * Batch and real-time pipelines * Medallion architecture * Analytics & Data Products * Tableau and ThoughtSpot * Semantic layers and KPI standardization

Pediatric Associates

Sr Data Engineer

San Pedro, CA · On-site

$116K - $140K/yr

The ideal candidate can translate business needs into technical specifications, write efficient SQL and Python code, and apply modern data engineering best practices across cloud-based environments.

Brighton

Data Engineer

City Of Industry, CA · On-site

$90K - $120K/yr

This is a small, hands-on data team, so the role extends beyond writing SQL and Python. You'll help ... The kind of engineer who will do well at Brighton You don't need to be a dedicated DevOps engineer ...

Pediatric Associates

Data Engineer

San Pedro, CA · On-site

$116K - $140K/yr

Develop efficient, well-structured SQL queries and data transformation logic to support analytics ... Strong programming skills in Python or another modern scripting language required. * Experience ...

OSTechnical

Be Seen First

Data Engineer

Irvine, CA · On-site

$100K - $115K/yr

Design and develop ETL/ELT pipelines using Snowflake, dbt, Matillion, and Python. * Integrate data ... Hands-on experience with Snowflake and advanced SQL. * Experience with dbt, Matillion, or similar ...

K&K Global Talent Solutions

Data Architect

Fountain Valley, CA · On-site

$69.25 - $89/hr

... engineering, ETL, data warehousing, cloud modernization and AI/ML solutions. Technical Skills * Strong expertise in Informatica PowerCenter, IDMC/IICS, PL/SQL, SQL, Python and Unix/Linux, with hands ...

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All JobsSql Python Data Engineer JobsSql Python Data Engineer Jobs in Los Angeles, CA

Sql Python Data Engineer information

See Los Angeles, CA salary details

$47.9K

$139.8K

$191.3K

How much do sql python data engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for sql python data engineer in Los Angeles, CA is $139,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,400.00 and $148,200.00 per year, depending on experience, location, and employer.

What is a SQL Python data engineer?

SQL Python Data Engineers are professionals who design, build, and maintain systems for collecting, storing, and analyzing large volumes of data, primarily using SQL and Python. They create data pipelines, optimize queries, and ensure data is accessible and reliable for analytics and business needs. Their work often involves collaborating with data scientists, analysts, and IT teams to support data-driven decision-making within an organization.

What are the key skills and qualifications needed to thrive as a SQL Python data engineer?

To thrive as a SQL Python Data Engineer, you need expertise in database design, advanced SQL querying, and proficiency in Python programming, often backed by a degree in computer science or a related field. Familiarity with data warehousing tools, ETL frameworks, cloud platforms (like AWS or Azure), and certifications such as AWS Certified Data Analytics are commonly expected. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate with teams and translate business needs into technical solutions. These skills ensure the efficient management, transformation, and delivery of reliable data for organizational decision-making.

How do SQL Python data engineers typically collaborate with data scientists and analysts within a project team?

SQL Python Data Engineers play a crucial role in enabling data scientists and analysts to access clean, reliable data. They are responsible for designing, building, and maintaining data pipelines that transform raw data into usable formats. Collaboration often involves working closely with data scientists to understand their data requirements and optimizing queries or scripts for performance. Regular communication and agile meetings are common, ensuring that data infrastructure supports evolving analytical needs. This partnership ensures that downstream users receive timely, accurate datasets for modeling, reporting, and decision-making.

What is the difference between Sql Python Data Engineer vs Data Analyst?

AspectSql Python Data EngineerData Analyst
Required SkillsSQL, Python, ETL, data modeling, cloud platformsSQL, Excel, data visualization, basic statistics
Work EnvironmentData pipelines, backend systems, cloud infrastructureReporting, dashboards, business insights
CertificationsData engineering certifications (e.g., Google Cloud, AWS)Data analysis or visualization certifications (e.g., Tableau, Excel)
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare

The Sql Python Data Engineer focuses on building and maintaining data pipelines, working with large datasets, and ensuring data accessibility for organizations. In contrast, Data Analysts primarily interpret data, create reports, and provide insights to support business decisions. While both roles require SQL skills, data engineers emphasize programming and infrastructure, whereas data analysts focus on analysis and visualization.

What cities near Los Angeles, CA are hiring for Sql Python Data Engineer jobs?

Cities near Los Angeles, CA with the most Sql Python Data Engineer job openings:

Sql Python Data Engineer jobs near you
Infographic showing various Sql Python Data Engineer job openings in Los Angeles, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $139,771 per year, or $67.2 per hour.

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

City Of Industry, CA

Motion Recruitment
Recruiting and Staffing Services • 501 - 1,000 employees
Learn more about Motion Recruitmentexternal

$115K - $138K/yr

Full-time

Posted 20 days ago

Key responsibilities

  • Design, build, and maintain production-grade data pipelines and transformations

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

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

Job description

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

City of Industry, CA | Full-Time

Our client is a growing organization seeking a Data Engineer to 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 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

Required Qualifications

  • Strong SQL skills, including complex joins, window functions, aggregations, NULL handling, and understanding of data grain

  • Hands-on Python development experience, including maintaining code running 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

Preferred Qualifications

  • Experience with Snowflake

  • Experience with Microsoft Azure

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

  • Terraform or other Infrastructure-as-Code experience

  • Experience working with multi-tenant or customer-facing data

  • Experience integrating with or reverse-engineering legacy and third-party systems

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

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

AI & Modern Engineering

The engineering team incorporates AI-assisted tools into 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 they verify results, identify incorrect assumptions, and validate technical solutions before putting them into production.

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