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Full Time Remote Azure Data Engineer Jobs in California

Lead Data Engineer

Alameda, CA · Remote

$155K - $175K/yr

Experience & SkillsYou'llBring * 10+ years of data engineering experience maintaining data platform ... CA Pay Range is $155,000 - $175,000 annually #LI-LO1 #LI-Remote Full time and Part time associates ...

Posted today

Data Engineer III

Irvine, CA · On-site +1

$160K - $180K/yr

Job Brief: The Data Engineer III will lead the development and maintenance of our data ... This is a remote position open to candidates based in the United States. Compensation: The salary ...

Data Engineering Manager

Pasadena, CA · On-site +1

$172K - $206K/yr

Founded in 2006, Spokeo has built a dedicated, remote-first team with an average tenure of 6.9 ... solutions (AWS, Azure) * 5+ years of experience with big data technologies (Spark, Hadoop ...

We are seeking a highly skilled and experienced Data Engineering Lead/Architect to join our dynamic ... Employment Type: FULL_TIME

Senior Data Engineer

Los Angeles, CA · On-site +1

$160K - $190K/yr

For those who reside full-time in NYC, SF, or LA: we have a hybrid work policy of three days in the ... remote work days. To learn more about the work we do at EDO, please visit EDO Press . The Role As a ...

Data Product Manager

San Diego, CA · On-site +1

$120K - $140K/yr

Remote or Hybrid is not available. Key Responsibilities: * Own and manage the data engineering ... Hands-on familiarity with Databricks, dbt, Fivetran, Kafka, Census, Azure Data Services, SSIS, ...

Founded in 2006, Spokeo has built a dedicated, remote-first team with an average tenure of 6.9 ... solutions (AWS, Azure) * 5+ years of experience with big data technologies (Spark, Hadoop ...

Data Platform Engineer

Santa Cruz, CA · On-site +1

$132K - $158K/yr

You'llwork across Azure, Databricks, and Microsoft Fabric to implement scalable, production-ready ... Remote(USA)or hybrid (Santa Cruz County, CA) Compensation:The estimated base salary range for this ...

$212K - $273K/yr

We transform KPI data into Sales Coaching with actionable next steps. ClosedWon will democratize ... Employment Type: FULL_TIME

We are seeking a highly skilled and experienced Data Engineering Lead/Architect to join our dynamic ... AWS, Azure, or GCP) and associated tools for data storage, processing, and orchestration. • ...

Build and maintain pipelines using Azure Data Factory and Synapse / Fabric Pipelines. * Manage source control, branching, and deployment using Git and Azure DevOps. * Run client-facing workshops ...

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Showing results 1-20

Full Time Remote Azure Data Engineer information

What is the difference between Full Time Remote Azure Data Engineer vs Full Time Remote Data Analyst?

AspectFull Time Remote Azure Data EngineerFull Time Remote Data Analyst
Required CredentialsAzure certifications, SQL, Python, cloud skillsSQL, Excel, data visualization tools, sometimes certifications
Work EnvironmentCloud platforms, data pipelines, codingData interpretation, reporting, dashboards
Industry UsageTech, finance, healthcare, retailMarketing, finance, healthcare, retail
Common Search/ComparisonYesYes

Azure Data Engineers focus on building and maintaining data pipelines using Azure cloud services, requiring technical skills and certifications. Data Analysts interpret data, create reports, and visualize insights, often using different tools. While both roles work with data, their responsibilities and skill sets differ significantly, making this comparison useful for job seekers exploring remote opportunities in data roles.

What are the most commonly searched types of Remote Azure Data Engineer jobs in California? The most popular types of Remote Azure Data Engineer jobs in California are:
What cities in California are hiring for Full Time Remote Azure Data Engineer jobs? Cities in California with the most Full Time Remote Azure Data Engineer job openings:
AI Data Engineer - Scientific Data Platforms (Remote)

AI Data Engineer - Scientific Data Platforms (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$35 - $38/hr

Full-time

Posted 23 hours ago


Job description

Pay Rate Low: 35 | Pay Rate High: 40
Our client is a leading global biotechnology and pharmaceutical organization driven by a mission to innovate, continuously advance science, and ensure everyone has access to the healthcare they need.
Title: AI Data Engineer - Scientific Data Platforms
Location: Remote, Must work PST
Pay rate: $35-38/hr (Depends on experience level)
Schedule: Full-time (40 hours/week)
Duration: 1-year contract, (Plus benefits)
Position Overview
This role addresses a critical need in scaling our AI models for drug discovery by building largely automated, scalable, agent-driven data ingestion and curation pipelines for genomics data. This includes metadata inference, constructing performant query architectures, and transforming high-dimensional datasets (e.g., single-cell omics, clinical trials) into AI-ready training formats.
Key Responsibilities
  • Build an agentic data ingestion pipeline and move beyond bespoke steps toward agents that teams can reliably use as a shared, deployed service.
  • Triage and prioritize incoming requests to ingest specific datasets. Clean and organize data, building the first-pass cleaning and organization steps into the agentic flow.
  • Validate cross-modal linkage. Add automated checks that catch when ingested data does not connect correctly and flag low-quality or mismatched records.
  • Version every dataset, retaining and making prior versions addressable. Preserve raw data and provenance, ensuring agent workflows log validation and transformation steps so lineage is fully traceable.
  • Partner with AI, software engineering, and computational biology groups to co-define data standards and conventions.

Qualifications & Requirements
  • Demonstrated experience building multi-agent workflows or LLM workflows using tools/frameworks such as LangGraph or LlamaIndex, including tool/function calling and asynchronous task execution.
  • Strong Python skills for data manipulation, working with APIs and databases, and handling heterogeneous data formats.
  • Familiarity with dataset versioning approaches (e.g., DVC, lakeFS, or equivalent).
  • Comfortable with or showing a strong willingness to learn common omics data formats like AnnData, H5AD, and TileDB.
  • No deep bioinformatics expertise required; just a basic conceptual understanding of different modalities (e.g., RNA-seq vs. scRNA-seq vs. WES; genomics vs. transcriptomics vs. proteomics vs. metabolomics).
  • Comfortable writing unit and functional tests to ensure data processing workflows are reliable and reproducible.
  • Degree in a technical field or equivalent practical experience.
  • Must be Authorized to work in the United States without Sponsorship.
Nice to Have
  • Experience deploying agent workflows as a shared service (e.g., FastAPI or MCP endpoints).
  • Exposure to cloud platforms (AWS, GCP) and containerization (Docker).
  • Familiarity with scientific workflow managers such as Nextflow or Snakemake.

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