Software Engineer - Remote

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections when posting has real specific content. We need to extract content. The posting includes: - Intro paragraph about Optum Tech, remote flexibility, office requirement for Minneapolis or DC area (4 days/week). That's about the role? Could be "About the role". We'll put that in

. - Primary Responsibilities: list of bullet points (multiple lines). We'll put under

Responsibilities

with

• each. - Required Qualifications: list of bullet points. Could be under

  Requirements

  or

  Qualifications

  . The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide which to use. There's both Required Qualifications and Preferred Qualifications. Also there is "AI Skills And Usage Expectations". Could be Skills. We need to preserve all substantive info. We'll create sections: - About the role: intro paragraph(s) about company, remote flexibility, office requirement. - Responsibilities: list of primary responsibilities. - Requirements: maybe Required Qualifications. - Qualifications: maybe Preferred Qualifications? Or we could combine Required and Preferred under Qualifications? But we have both headings. Could do Requirements for required, Qualifications for preferred. Or Skills for AI skills usage. - Skills: maybe AI Skills And Usage Expectations. - Benefits: mention benefits package, incentive and recognition programs, equity stock purchase and 401k contribution. - Pay: salary range $72,800 - $130,000 annually. - Schedule: remote flexibility, office requirement for Minneapolis/DC (4 days/week). Could be schedule. We must not include sections with filler like "commensurate with experience". We have actual content. We must not repeat job title as heading. No Job ID. We must remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. So we need to cut out the EEO statement, drug test, mission statements, etc. Also remove "Application Deadline: ..." and "At UnitedHealth Group, our mission..." etc. Also remove "We comply with all minimum wage laws as applicable." maybe keep? It's generic but maybe considered boilerplate. Safer to remove. We need to preserve all substantive information: responsibilities, qualifications, preferred qualifications, AI skills usage, benefits, pay, schedule (remote flexibility, office requirement). Also the intro about Optum Tech and remote flexibility. Let's extract. Intro paragraph(s): "Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week." We'll keep that as About the role. Responsibilities list: - Build, enhance, and support Azure data pipelines and data solutions for the Identity Management rebuild and existing application support - Develop and support data pipelines using Azure Databricks, Azure Data Factory, PySpark, Python, and Git-based development practices across development, staging, and production environments - Troubleshoot data issues, improve pipeline reliability, and contribute to performance tuning and cost optimization activities - Support ingestion, transformation, serving, monitoring, and data quality activities for distributed processing workloads while following data governance, privacy, and security expectations - Support the build and operationalization of custom AI agents to assist with development, testing, documentation, data validation, monitoring, production support, runbook execution, and data workflow automation - Use Databricks Genie, GitHub Copilot, Microsoft 365 Copilot, and other enterprise-approved GenAI tools to accelerate pipeline development, automation, troubleshooting, documentation, analysis, and decision-making workflows - Maintain a minimum of 90% weekly usage of approved AI tools and leverage AI tools and agents to enhance coding, documentation, data analysis, testing, and delivery workflows - Collaborate with stakeholders, platform engineering, analytics, and application teams to support delivery priorities and communicate risks, dependencies, and progress clearly - Stay current with evolving AI capabilities and apply them to improve delivery quality, efficiency, innovation, and responsible engineering practices We'll put each as
• . Required Qualifications list: - 5+ years of hands-on data engineering experience building, supporting, and operating data pipelines and data platforms - Azure Databricks experience, including pipeline development, job monitoring, workload support, performance tuning, and cost-aware development practices - Azure Data Factory experience with pipeline orchestration, scheduling, dependency management, monitoring, and operational support - PySpark experience for distributed data processing, transformations, data quality validation, and performance tuning - Git experience including CI/CD basics, version control, pull request workflows, branching strategies, and release support - Experience supporting performance tuning and cost optimization activities for cloud data pipelines, Databricks workloads, and distributed processing jobs - Basic working understanding of data governance, data security, access controls, privacy, and enterprise compliance concepts - Baseline proficiency with enterprise-approved AI tools including GitHub Copilot, Microsoft 365 Copilot, Databricks Genie, and other approved GenAI platforms - Proficiency in Python for programming, automation, data processing, and scripting - Proven good problem-solving skills with the ability to perform root cause analysis, troubleshoot data pipeline issues, and follow reliable engineering practices - Proven good communication and collaboration skills, with the ability to share technical updates, risks, dependencies, and delivery progress clearly Preferred Qualifications list: - Prior experience building Identity data pipelines, identity resolution pipelines, consumer profile data pipelines, member/customer identity management solutions, or similar identity-matching and entity-resolution capabilities - Hands-on experience building, configuring, or supporting custom AI agents to assist with development, testing, documentation, data validation, monitoring, and data workflow execution - Hands-on experience using Databricks Genie and GitHub Copilot for pipeline development, debugging, documentation, automation, and development productivity improvements - Data engineering experience with Python, PySpark, Azure Databricks, Azure Data Factory, and Git in a cloud data platform environment - Healthcare, insurance, consumer profile, or enterprise identity data experience is preferred AI Skills And Usage Expectations list (maybe under Skills): - All contractor resources are expected to demonstrate baseline proficiency with enterprise-approved AI tools and maintain consistent weekly usage of GitHub Copilot, Microsoft 365 Copilot, Databricks Genie, and other approved GenAI platforms, where applicable - Apply AI tools to improve coding, documentation, data analysis, testing, monitoring, troubleshooting, decision-making workflows, and delivery quality and velocity - Use or support custom agents for pipeline development, automated test creation, data quality validation, failure detection, incident triage, runbook execution, and operational reporting while staying current with evolving AI capabilities, features, and enterprise guidance Benefits: - In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). - No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. We could combine. Pay: - The salary for this role will range from $72,800 - $130,000 annually based on full-time employment. Schedule: - You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. - For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. - All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy (maybe keep as schedule? It's policy but could be schedule). Might keep. We need to avoid duplication: remote flexibility already in About the role; but schedule section could still include the office requirement. Might be okay. We must not include filler like "commensurate with experience". Not present. Now produce HTML fragment:

  About the role

  Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

  Responsibilities

  • Build, enhance, and support Azure data pipelines and data solutions for the Identity Management rebuild and existing application support
  • Develop and support data pipelines using Azure Databricks, Azure Data Factory, PySpark, Python, and Git-based development practices across development, staging, and production environments
  • Troubleshoot data issues, improve pipeline reliability, and contribute to performance tuning and cost optimization activities
  • Support ingestion, transformation, serving, monitoring, and data quality activities for distributed processing workloads while following data governance, privacy, and security expectations
  • Support the build and operationalization of custom AI agents to assist with development, testing, documentation, data validation, monitoring, production support, runbook execution, and data workflow automation
  • Use Databricks Genie, GitHub Copilot, Microsoft 365 Copilot, and other enterprise-approved GenAI tools to accelerate pipeline development, automation, troubleshooting, documentation, analysis, and decision-making workflows
  • Maintain a minimum of 90% weekly usage of approved AI tools and leverage AI tools and agents to enhance coding, documentation, data analysis, testing, and delivery workflows
  • Collaborate with stakeholders, platform engineering, analytics, and application teams to support delivery priorities and communicate risks, dependencies, and progress clearly
  • Stay current with evolving AI capabilities and apply them to improve delivery quality, efficiency, innovation, and responsible engineering practices

  Requirements

  • 5+ years of hands-on data engineering experience building, supporting, and operating data pipelines and data platforms
  • Azure Databricks experience, including pipeline development, job monitoring, workload support, performance tuning, and cost-aware development practices
  • Azure Data Factory experience with pipeline orchestration, scheduling, dependency management, monitoring, and operational support
  • PySpark experience for distributed data processing, transformations, data quality validation, and performance tuning
  • Git experience including CI/CD basics, version control, pull request workflows, branching strategies, and release support
  • Experience supporting performance tuning and cost optimization activities for cloud data pipelines, Databricks workloads, and distributed processing jobs
  • Basic working understanding of data governance, data security, access controls, privacy, and enterprise compliance concepts
  • Baseline proficiency with enterprise-approved AI tools including GitHub Copilot, Microsoft 365 Copilot, Databricks Genie, and other approved GenAI platforms
  • Proficiency in Python for programming, automation, data processing, and scripting
  • Proven good problem-solving skills with the