Senior Engineering Intelligence Analyst

Role Summary
We are looking for a hands-on analytics engineer to build, maintain, and evolve Five9’s engineering
intelligence platform. You will be the technical engine behind a growing function that provides data-
driven insights to engineering leadership across a portfolio of 1,000+ features and $100M+ in
engineering investment.
You will work with data from Jira, Jellyfish, Salesforce, and other systems to build automated pipelines,
interactive dashboards, and analytical tools that enable faster, smarter decisions. This role is ideal for
someone who combines strong data engineering fundamentals with a passion for making data
accessible and actionable—someone who gets excited about building a pipeline as much as crafting a
clear visualization.

Responsibilities
Dashboard Development & Maintenance (40%)
Build and maintain sophisticated, interactive dashboards in Looker covering feature delivery
predictions, FTE allocation, resource contention, and portfolio health.
Migrate existing HTML-based dashboards to the enterprise Looker platform while preserving and
enhancing analytical depth.
Design intuitive, self-service visualizations that enable engineering leaders to explore data and
answer their own questions.
Implement and analyze DORA metrics (Deploy Frequency, Lead Time, Change Failure Rate, MTTR) to
measure and improve DevOps performance.
Implement alerting and anomaly detection to proactively surface risks (e.g., feature slippage,
resource over-allocation, stale work items).

Data Engineering & Integration (35%)
Build and maintain robust, automated data pipelines integrating Jira (REST API, Structure exports),
Jellyfish APIs, Salesforce, and other internal systems into Google BigQuery.
Write and optimize complex SQL queries and Python scripts to extract, transform, and load data.
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Build and maintain scalable and efficient data models using LookML, establishing a “source of truth”
for engineering metrics.
Implement data quality checks, automated validation, and monitoring to ensure accuracy and
freshness with a near-real-time SLA.
Optimize query performance and data models for sub-second dashboard response times.
Analysis & Insight Support (25%)
Collaborate with engineering and product teams to analyze data from Jira and Jellyfish, providing
insights into team performance, project delivery, and resource allocation.
Engage in business analysis to understand stakeholder needs, gather requirements, and translate
them into technical specifications for data models and reports.
Support leadership in preparing executive-ready analyses and insight decks for QBRs and other
strategic reviews.
Document data lineage, calculation methodologies, and dashboard logic for transparency and
auditability.

Skills, Competencies, and Qualifications
Required
5-8 years of experience in analytics engineering, data engineering, business intelligence, or a related
technical analytics role.
Expert-level proficiency in SQL (complex joins, window functions, CTEs, performance optimization).
Proficiency in Python for data processing (e.g., pandas, requests, scheduled jobs).
Hands-on experience with Looker, including LookML data modeling, advanced dashboard design,
and performance optimization.
Experience building and maintaining ETL/ELT pipelines with REST API data sources.
Deep understanding of the software development lifecycle (SDLC), Agile methodologies, and how
engineering organizations operate.
Strong data visualization skills with a proven ability to design dashboards that tell a clear story.

Preferred
Experience with Jira APIs, Jira Structure, and the Atlassian ecosystem at scale.
Familiarity with Engineering Management Platforms like Jellyfish.
Experience with Looker and LookML.
Experience with cloud data platforms, specifically Google BigQuery.
Exposure to engineering metrics (DORA, flow efficiency, cycle time, throughput).
HTML/JavaScript skills for custom visualizations and rapid prototyping