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Software Engineer Data Analyst Jobs in California

The Staff Software Engineer, Data will design and build scalable data infrastructure to support ... scale analytics workloads • Pioneer data architecture by integrating recent innovations in ...

The Staff Software Engineer, Data will design and build scalable data infrastructure to support ... scale analytics workloads • Pioneer data architecture by integrating recent innovations in ...

Experience optimizing in-stream, big data processing and analytics frameworks like Apache Kafka ... Software Engineer/Senior: $160,000.00 - $265,000.00/per year Your actual level and base salary will ...

Experience optimizing in-stream, big data processing and analytics frameworks like Apache Kafka ... Software Engineer/Senior: $160,000.00 - $265,000.00/per year Your actual level and base salary will ...

Lead cross-functional collaboration with Analytics, Product, and Engineering to deliver reliable ... software engineering. * 7+ years of experience in building large scale data solutions. * Strong ...

Showing results 41-60

Software Engineer Data Analyst information

See California salary details

$43.9K

$128K

$175.2K

How much do software engineer data analyst jobs pay per year?

As of Aug 8, 2026, the average yearly pay for software engineer data analyst in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

What is the difference between Software Engineer Data Analyst vs Data Scientist?

AspectSoftware Engineer Data AnalystData Scientist
Required CredentialsBachelor's in CS, Data Analysis, or related; programming skillsBachelor's or higher in CS, Statistics, or related; advanced analytics skills
Work EnvironmentSoftware development teams, data analysis projectsResearch, modeling, predictive analytics teams
Employer & Industry UsageTech companies, finance, healthcareTech firms, research institutions, finance
Common Search & ComparisonOften compared for data roles involving coding and analysisMore focused on predictive modeling and research

The main difference between a Software Engineer Data Analyst and a Data Scientist lies in their focus and skill set. Software Engineers Data Analysts primarily develop data tools and analyze data using programming, while Data Scientists focus on building predictive models and advanced analytics. Both roles require strong technical skills, but Data Scientists typically have more expertise in statistics and machine learning.

How do software engineer data analysts typically collaborate with other teams to deliver data-driven solutions?

Software Engineer Data Analysts work closely with cross-functional teams, including data scientists, product managers, and software developers, to collect requirements and translate business needs into actionable analytics solutions. They often participate in regular meetings to align on project goals, share progress, and troubleshoot data integration challenges. Effective communication is key, as they must explain technical findings to non-technical stakeholders and ensure that the data pipelines and dashboards they develop meet end-user needs. This collaborative environment provides opportunities to broaden technical skills and gain insights into various business functions.

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

To thrive as a Software Engineer Data Analyst, you need strong programming skills (such as Python or Java), a solid understanding of data structures and algorithms, and a background in statistics or computer science. Proficiency in SQL, data visualization tools (like Tableau or Power BI), and experience with big data platforms (such as Hadoop or Spark) are typically required, along with relevant certifications. Analytical thinking, problem-solving ability, and effective communication help you translate complex data into actionable insights. These skills ensure you can extract, analyze, and communicate data-driven solutions that support business objectives.

What is a software engineer data analyst?

A Software Engineer Data Analyst is a professional who combines software engineering skills with data analysis expertise to extract insights from data and build applications or tools for data processing. They typically design, develop, and maintain software systems that collect, store, and analyze large datasets. Their role often involves writing code to automate data workflows, create dashboards, and perform statistical analyses. These professionals work closely with other engineers, data scientists, and business stakeholders to support data-driven decision making.
What cities in California are hiring for Software Engineer Data Analyst jobs? Cities in California with the most Software Engineer Data Analyst job openings:

Senior Software Engineer, Data

The Consensus

San Francisco, CA • On-site

$180 - $225/hr

Other

Medical, Dental, Vision

Posted 3 days ago

New


Job description

fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

About this role:

As a Senior Data Engineer at fal, you will build the data infrastructure that turns our internal systems and external vendor relationships into a clear picture of cost, margin, and performance. Your work spans both edges of our stack - the production infrastructure that runs every model invocation, and the partner APIs and compute vendors whose costs we need to reason about in near real-time.

This role sits at the intersection of software engineering and data engineering. You\'ll partner closely with Infra to safely instrument core systems, design a low-latency analytical write path, and stand up the ingestion pipelines that unlock cost, margin, and infrastructure analytics for the entire company. You will be a force multiplier - freeing up product engineers and infra to focus on what they do best while giving the data team the foundations it needs to move fast.

What you\'ll do
  • Instrument fal\'s core infrastructure to capture CPU, GPU, and request-level signals, working alongside our infra team to land changes safely in critical paths.

  • Build ingestion pipelines from partner APIs, compute vendors, and internal services into BigQuery and a new low-latency analytical store (e.g., ClickHouse).

  • Design and operate the ETL backbone that powers cost, margin, and usage analytics with durable, observable pipelines.

  • Stand up a lightweight, low-latency write path that the data team and product engineers can target directly for analytics-grade telemetry.

  • Partner with infra, data and product engineering to define data contracts and instrumentation standards, and act as the connective tissue between operational systems and the analytics layer.

What we are looking for
  • 5+ years of experience as a software or data engineer, with a software-engineering-heavy track record (Python, Go, or similar)

  • Demonstrated ability to ship code into critical production infrastructure safely, including familiarity with database performance, query patterns, and incident risk.

  • Hands-on experience building ingestion pipelines into a warehouse (BigQuery, Snowflake, Redshift) and at least one low-latency analytical store (ClickHouse, Druid, Pinot, or similar).

  • Strong SQL and working proficiency in dbt and orchestration tooling (Dagster, Airflow, Prefect).

  • Track record of partnering across teams (infra, product engineering, data) and translating business questions into durable systems.

  • Bias for action and comfort working in fast-moving, ambiguous environments.

Nice-to-haves
  • Experience instrumenting GPU/accelerator workloads or other infrastructure-cost-heavy systems.

  • Exposure to FinOps or infrastructure cost modeling at a cloud-native company.

  • Experience with developer-facing API products or platforms.

  • Early-stage or fast-scaling startup experience.

Compensation
  • $180,000-225,000 plus equity + benefits (This range is across 2 levels Senior and Staff)

Location
  • San Francisco, CA (willing to consider remote for Senior and Staff levels)

What we offer at fal
  • Interesting and challenging work

  • A lot of learning and growth opportunities

  • We are currently hiring in downtown San Francisco.

  • We offer relocation assistance to San Francisco.

  • Health, dental, and vision insurance (US)

  • Regular team events and offsites

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