[Hiring] Sr. Engineering Insights Analyst @Alteryx

Role Description

Alteryx is searching for a Sr. Engineering Intelligence Analyst (Engineering Insights Team). This position is remote-friendly.

We are building a data-driven understanding of how our engineering organization operates, and we’re looking for a Data Analyst focused on Engineering Intelligence to help us do it. This role sits at the intersection of engineering, data, and operational excellence. Your mission is to transform engineering signals into insights that help us improve software quality, productivity, reliability, and cost efficiency.

You will analyze data from across the software development lifecycle (SDLC), from pull requests and CI/CD pipelines to service reliability metrics and incident management, and translate it into dashboards and insights that guide engineering leaders.

If you are passionate about understanding how engineering organizations work and how they can improve, this role is for you.

What You’ll Work On

• Engineering Effectiveness & SDLC Metrics
  • Development & productivity
  • Pull request volume and cycle time
  • Code review latency
  • Deployment frequency
  • Lead time for changes
  • Change failure rate
  • Reliability & operations
  • SLO / SLA performance
  • Incident and escalation patterns
  • Engineering quality
  • Defect trends
  • Incident root causes
  • Platform adoption
  • Usage of internal platforms and services
  • Adoption of engineering standards and best practices
  • Engineering cost efficiency
  • Infrastructure cost trends
  • Cost per service / team
  • Efficiency of engineering investments
• Build Data Products for Engineering
  • Engineering health dashboards
  • Service reliability dashboards
  • Operational insights for engineering managers
  • Executive views of engineering performance
  • Adoption dashboards for internal platforms
• Data Pipelines & Analysis
  • Writing advanced SQL queries to analyze engineering data
  • Building lightweight Python pipelines to aggregate and process signals
  • Integrating data from sources such as:
    • Git repositories (PRs, commits)
    • CI/CD systems
    • Incident management systems
    • Observability platforms
    • Ticketing systems
    • Cost management tools
  • Ensuring that engineering metrics are accurate, consistent, and trusted across the organization.
• Generate Insights That Drive Decisions
  • Identifying bottlenecks in the development process
  • Detecting reliability risks early
  • Understanding operational load across teams
  • Measuring whether internal platform investments are working
  • Connecting engineering activity with infrastructure costs
• Collaborate Across Engineering
  • Engineering managers
  • Platform and infrastructure teams
  • DevOps / SRE
  • FinOps
  • Engineering leadership

Qualifications

• Strong SQL skills
• Experience using Python for data analysis or pipelines
• Experience building dashboards in Superset, Tableau, Looker, or similar BI tools
• Experience working with complex operational datasets
• Familiarity with data modeling and metric definitions

Requirements

• Comfortable working with engineering concepts such as:
  • Pull Requests (PRs)
  • CI/CD pipelines
  • Software Development Lifecycle (SDLC)
  • Service Level Objectives (SLOs)
  • Incident management
  • Escalation tickets
  • Service reliability metrics
• Enjoy working closely with engineers and understanding how systems are built and operated.
• Strong analytical thinking
• Ability to translate ambiguous questions into measurable metrics
• Ability to communicate insights clearly to technical and leadership audiences
• Strong attention to data quality and metric consistency

Benefits

• Growth mindset support for associates
• Commitment to a diverse, equitable, and inclusive workplace