Senior Analytics Engineer

Rocket Lab is an end-to-end space company delivering responsive launch services, complete spacecraft design and manufacturing, payloads, satellite components, and more – all with the goal of opening access to space. The rockets and satellites we build and launch enable some of the most ambitious and vital space missions globally, supporting scientific exploration, Earth observation and missions to combat climate change, national security, and exciting new technology demonstrations.

Our Electron rocket has become the second most frequently launched U.S. rocket annually and has delivered more than 230 satellites to orbit, all while we work to develop Neutron, our upcoming medium-lift, reusable launch vehicle for larger constellation deployment. Our Space Systems business designs and builds our extensive line of satellites, payloads, and their components, including spacecraft that have been selected to support NASA missions to the Moon and Mars and components used on the James Webb Space Telescope.

Rocket Lab’s IT team is responsible for how our global teams access information and run operations across our computer systems, networks, and devices. Our hardworking IT team is a group of flexible problem‑solvers working in a fast‑paced environment, but who also thrive under the challenge of supporting all of our proprietary systems and people, from finance to launch operations.

Based onsite at Rocket Lab’s global headquarters in Long Beach, CA, the Senior Analytics Engineer I, as part of the Business Intelligence team, is responsible for driving strategic initiatives with measurable business impact, architecting scalable data solutions, and shaping team technical direction. This role balances hands‑on technical work including mentoring (70%), cross‑functional collaboration (20%), and continuous learning (10%). You'll design data architectures, establish engineering standards, lead analytical initiatives, and mentor team members while delivering enterprise‑level solutions that drive business strategy and operational excellence.

• Data Engineering & Architecture
  • Design and build scalable data architectures using advanced SQL, dbt frameworks, and multiple ETL/ELT tools (Azure Data Factory, SSIS, Databricks or modern open‑source tools)
  • Implement metadata‑driven pipelines at scale and lead data modeling efforts across multiple subject areas
  • Optimize performance at enterprise scale using cloud/on‑prem advanced features, Python, and streaming/real‑time data patterns
• Business Intelligence & Analytics
  • Lead analytical initiatives and design comprehensive KPI frameworks that influence business strategy and establish RBAC/RLS security
  • Design semantic layers and enterprise data models using TDML, Power BI (DAX, M Query), Tableau, and Grafana
• Data Governance & Quality
  • Design and implement data governance frameworks including metadata management, privacy policies, and retention standards
  • Lead incident response for data quality issues, conduct root cause analysis, and deliver remediation plans
  • Conduct peer reviews of SQL, dbt, Python, DAX, and M Query code, ensuring adherence to best practices
• Other Collaborations
  • Mentor junior engineers on engineering best practices, performance optimization, and visualization design principles
  • Partner with Director‑level stakeholders and business leaders to translate requirements into technical solutions
  • Participate in sprint planning, technical design reviews, architecture discussions, and roadmap planning
  • Other duties as reasonably required

• 5+ years of experience and a bachelor's degree or equivalent experience with a high school diploma or GED (9+ total years)
• Technical Expertise in the following:
  • Demonstrated expertise in analytics engineering or data platform development
  • Expert‑level data modeling and architecture design across multiple subject areas
  • Proficiency with ETL/ELT tools:
    Azure Data Factory, SSIS, Databricks, and dbt or modern open‑source tools
  • Hands‑on Kubernetes experience (deployment, cluster management, best practices)
  • Advanced Power BI development (DAX, M Query, TDML, semantic layers)
  • Cloud platform…