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Remote Data Engineer Jobs in Berkeley, CA (NOW HIRING)

The role We're looking for a Senior Data Engineer to help the team deliver data science services ... We are a remote-first company for most positions so you may work from anywhere you like in the U.S ...

Senior Data Engineer - Finance

San Francisco, CA · On-site +1

$124K - $169K/yr

We are looking for a Data Engineer - Finance to join our Data Engineering & Analytics team. Your ... We've been alerted to scammers posing as ŌURA recruiters, especially for remote roles. Please note:

Senior Data Engineer

San Francisco, CA · Remote

$165K - $220K/yr

As a Senior Data Engineer at Regard, you will own the design, development, and production deployment of the data services that power the Regard platform. From ingesting and standardizing clinical ...

Sr. Data Platform Engineer

San Francisco, CA · On-site +1

$134K - $161K/yr

Employee divides their time between in-office and remote work. Access to an office location is ... Experience as a Data Platform Engineer or ML/AI Engineer with significant handson work in Snowflake ...

We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

Showing results 41-60

Remote Data Engineer information

See Berkeley, CA salary details

$54.5K

$158.8K

$217.3K

How much do remote data engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for remote data engineer in Berkeley, CA is $158,830.00, according to ZipRecruiter salary data. Most workers in this role earn between $140,200.00 and $168,400.00 per year, depending on experience, location, and employer.

What does a remote data engineer do?

As a remote data engineer, you focus on collecting, storing, and organizing large amounts of information. You work from home to design, develop, and maintain systems for the mining, warehousing, and processing of data. A data engineer communicates with employers, clients, or other data professionals to assess the needs of the project and develop and implement solutions to meet those needs. Data engineers also take steps to manage current database architecture and make updates when needed. Remote engineers typically handle their responsibilities in a cloud-based environment using “big data” tools, such as Amazon Web Services (AWS) and SQL.

What is the difference between Remote Data Engineer vs Remote Data Analyst?

AspectRemote Data EngineerRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; SQL, Python, cloud certificationsBachelor's in Statistics, Data Science, or related; SQL, Excel, visualization tools
Work EnvironmentCollaborates with data engineering teams, cloud platforms, big data toolsWorks with business teams, dashboards, reporting tools
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare
Common Search IntentBuilding data pipelines, data infrastructureData reporting, insights, visualization

Remote Data Engineers focus on designing and maintaining data pipelines and infrastructure, often requiring programming and cloud skills. Remote Data Analysts interpret data, create reports, and provide insights using visualization tools. While both roles work with data, their responsibilities and skill sets differ, making each suited for different career paths within data teams.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote Data Engineers often work with cross-functional teams, including data scientists, analysts, and software engineers, many of whom may be located in different parts of the world. Collaboration is usually facilitated through project management tools, version control platforms, and regular virtual meetings. It’s common to have a mix of synchronous check-ins and asynchronous communication, allowing for flexible scheduling and efficient handoffs. Strong written communication skills and proactive status updates are essential for staying aligned with team objectives and project deadlines.

What is a remote data engineer?

A Remote Data Engineer is a professional who designs, builds, and maintains data pipelines, databases, and data processing systems while working from a location outside of a traditional office. They collaborate with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and made accessible efficiently and securely. Remote Data Engineers use programming languages like Python or Scala, work with technologies such as SQL, Hadoop, or cloud platforms, and address challenges related to data quality and scalability. Their remote role allows them to work for companies regardless of geographic location, often relying on virtual collaboration tools to stay connected with their teams.

What are the key skills and qualifications needed to thrive as a remote data engineer, and why are they important?

To thrive as a Remote Data Engineer, you need strong programming skills in languages like Python or Scala, expertise in SQL, data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Hadoop and Spark), and certifications in cloud or data engineering are highly valued. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive in a distributed environment. These competencies ensure reliable data pipelines, scalable solutions, and seamless teamwork, which are critical for organizational success in data-driven projects.
What are the most commonly searched types of Data Engineer jobs in Berkeley, CA? The most popular types of Data Engineer jobs in Berkeley, CA are:
What are popular job titles related to Remote Data Engineer jobs in Berkeley, CA? For Remote Data Engineer jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineer jobs in Berkeley, CA look for? The top searched job categories for Remote Data Engineer jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Remote Data Engineer jobs? Cities near Berkeley, CA with the most Remote Data Engineer job openings:
Infographic showing various Remote Data Engineer job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $158,830 per year, or $76.4 per hour.

Senior Data Engineer ID75059

AgileEngine

San Francisco, CA • On-site, Remote

$124K - $169K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you\'re looking for a place to grow, make an impact, and work with people who care, we\'d love to meet you!
ABOUT THE ROLE
We are looking for a Senior Data Engineer to design and build scalable data lakes, warehouses, and lakehouse architectures supporting a thematic research platform that processes large volumes of financial data daily. You will implement Python-based ETL/ELT pipelines, orchestrate workflows with Airflow, develop ingestion workflows from third-party APIs, and work with Snowflake, Spark, and AWS to deliver high-performance data infrastructure. The role combines hands-on engineering with technical consulting responsibilities, translating business goals into data architecture roadmaps.
WHAT YOU WILL DO
- Design and implement Python Data Engineering solutions;
- Design and build scalable Data Lakes, Data Warehouses, and Data Lakehouses;
- Design and implement robust ETL/ELT processes at scale using Python, incorporating modern pipeline orchestration tools like Airflow;
- Develop sophisticated ingestion workflows from diverse 3rd party APIs and data sources;
- Manage and optimize various file formats (Parquet, Avro, ORC) and columnar storage to ensure high-performance data retrieval;
- Work with AI development tools to support and accelerate ongoing development, machine learning initiatives and advanced analytics;
- Act as a technical consultant for stakeholders and leadership to gather requirements, understand business goals, and translate them into technical roadmaps;
- Work with Terraform and other tools to build AWS and on-prem infrastructure.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- Bachelor’s degree in computer science/engineering or other technical field, or equivalent experience;
- 5+ years of experience with Python (strong, hands-on Python experience is a must);
- 5+ years of experience with data processing, manipulation, and analytics libraries like Pandas, Polars, PySpark or DuckDB;
- 2+ years of experience with Big Data technologies (Spark, Snowflake);
- Expert-level knowledge of pipeline orchestration using Airflow or similar industry-standard tools;
- Deep understanding of Medallion Architecture, columnar file formats, and diverse database technologies (SQL, NoSQL, and Lakehouse architectures);
- Proven ability to work with 3rd party APIs for complex data ingestion tasks;
- Proficiency with modern Cloud platforms (AWS, GCP, Snowflake) and advanced SQL optimization;
- Exceptional soft skills with a proven ability to gather requirements from leadership and collaborate effectively across cross-functional teams;
- Excellence in optimizing complex data pipelines and troubleshooting data latency or consistency issues in massive datasets;
- A self-starter mindset, regularly investigating more efficient data architectures and AI development tools to improve pipeline performance;
- Taking pride in data integrity and the accuracy of the end-to-end pipelines and architectures you build;
- Strong communication skills for seamless global collaboration with stakeholders and distributed teams;
- Upper-intermediate English level.
NICE TO HAVES
- Familiarity with the fintech industry, understanding of financial data, regulatory requirements, and business processes specific to the domain;
- Documentation skills to document data pipelines, architecture designs, and best practices for knowledge sharing and future reference;
- OpenSearch, Elasticsearch;
- AWS Sagemaker Studio, Jupyter for analyze data;
- Terraform;
- Scala.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.