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Software Engineer Data Analyst Jobs in Austin, TX

ICON

Senior Software Engineer, Data

Austin, TX

$113K - $136K/yr

Develop and maintain large, high quality datasets that power machine learning models and analytical ... software development experience. * 5+ years of hands on experience managing and engineering data at ...

Acrisure

Software Engineer, Data (L1)

Austin, TX · On-site

$113K - $136K/yr

Software Engineer, Data (L1) Austin, TX (Onsite 4 days per week) Note: This is a full-time role and ... analytics and reporting platforms, and business processes that provide quality data, in a timely ...

Acrisure Innovation

Software Engineer, Data (L1)

Austin, TX · On-site

$113K - $136K/yr

Software Engineer, Data (L1) Austin, TX (Onsite 4 days per week) Note: This is a full-time role and ... analytics and reporting platforms, and business processes that provide quality data, in a timely ...

Acrisure Innovation

Software Engineer, Data (L1)

Austin, TX · On-site

$113K - $136K/yr

Software Engineer, Data (L1) Austin, TX (Onsite 4 days per week) Note: This is a full-time role and ... analytics and reporting platforms, and business processes that provide quality data, in a timely ...

ICON

Senior Software Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

Apply statistical and analytical techniques to assess dataset quality, identify gaps, and surface ... software development experience. * 5+ years of hands on experience managing and engineering data at ...

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All JobsSoftware Engineer Data Analyst JobsSoftware Engineer Data Analyst Jobs in Austin, TX

Software Engineer Data Analyst information

See Austin, TX salary details

$44.1K

$128.5K

$175.9K

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 Austin, TX is $128,545.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 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 near Austin, TX are hiring for Software Engineer Data Analyst jobs? Cities near Austin, TX with the most Software Engineer Data Analyst job openings:
Software Engineer Data Analyst jobs near you

Senior Software Engineer, Data

ICON

Austin, TX

$113K - $136K/yr

Full-time

Posted 21 days ago

Job description

ICON is looking for a Software Engineer to join our growing team. In this role, you will be responsible for designing, building, and maintaining the data infrastructure that powers our data-driven products and services.

Data Engineering Responsibilities

  • Design and build robust data pipelines to ingest, transform, and load data from a variety of internal and external sources.
  • Develop and maintain large, high quality datasets that power machine learning models and analytical products.
  • Build scalable data storage, processing, and serving infrastructure on cloud platforms.
  • Develop tooling and services for data labeling, data review, and dataset curation at scale.
  • Find and evaluate new external data sources - manage relationships with data partners and vendors.
  • Contribute to CI/CD practices and engineering standards across the data platform.

Data Science Responsibilities

  • Partner with ML engineers and researchers to design feature pipelines and experiment infrastructure.
  • Apply statistical and analytical techniques to assess dataset quality, identify gaps, and surface insights.
  • Develop efficient algorithms and data models to curate data and maintain high quality and consistency.
  • Design and evaluate metrics to measure dataset health and model readiness.
  • Translate ambiguous research questions into well defined data problems with measurable outcomes.

Minimum Qualifications

  • 7+ years of software development experience.
  • 5+ years of hands on experience managing and engineering data at scale.
  • Proficiency in Python, TypeScript and SQL.
  • Experience with cloud data services and storage technologies (e.g., S3, Redshift, BigQuery, Snowflake).
  • Familiarity with statistical analysis and core data science concepts (feature engineering, data distributions, model evaluation etc).
  • Degree in Computer Science, Statistics, a related technical field, or equivalent experience.
  • Strong problem solving skills with the ability to work independently and drive projects end-to-end.

Preferred Skills and Experience

  • Experience building large datasets for machine learning training and evaluation.
  • Proficiency with data science libraries (pandas, NumPy etc.).
  • AWS experience, including CDK or similar managed services.
  • Experience with workflow orchestration tools (Airflow, Prefect etc).
  • Experience with modern CI/CD workflows
  • Experience partnering with external organizations or managing 3rd party data vendors.

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