Asks for

The ad says“Experience with Agile and Test-Driven Development methodology.”
The ad says“Detailed knowledge of and substantial experience with data structures and algorithms.”
The ad says“Experience with Continuous Integration & Delivery and automation tools such as Jenkins, Artifactory, and Git.”
The ad says“Solid technical database knowledge across Hadoop, Python, and Snowflake — data modeling, performance tuning, cost governance, and large-scale query optimization.”
The ad says“Detailed knowledge of and substantial experience with data structures and algorithms.”
The ad says“Proficiency with Docker — authoring Dockerfiles, multi-stage builds, container registries, and integrating images into orchestration and CI/CD pipelines.”
The ad says“Experience with Continuous Integration & Delivery and automation tools such as Jenkins, Artifactory, and Git.”
The ad says“Solid technical database knowledge across Hadoop, Python, and Snowflake — data modeling, performance tuning, cost governance, and large-scale query optimization.”
The ad says“Experience with Continuous Integration & Delivery and automation tools such as Jenkins, Artifactory, and Git.”
The ad says“Hands-on Kubernetes experience — deploying data workloads, managing namespaces, debugging pods/logs/events, and tuning resource requests and limits.”
The ad says“10+ years of software development and data engineering experience with very high proficiency in Python (production-grade: packaging, testing, CI/CD).”
The ad says“Solid technical database knowledge across Hadoop, Python, and Snowflake — data modeling, performance tuning, cost governance, and large-scale query optimization.”
The ad says“Experience working with large-scale data warehouse and data lake solutions such as Teradata, Snowflake, Redshift, and Hadoop/HDFS-based ecosystems.”
The ad says“Solid technical database knowledge across Hadoop, Python, and Snowflake — data modeling, performance tuning, cost governance, and large-scale query optimization.”
The ad says“Hands-on experience with Tableau (published data sources, extract schedules, performance optimization).”
The ad says“Experience working with large-scale data warehouse and data lake solutions such as Teradata, Snowflake, Redshift, and Hadoop/HDFS-based ecosystems.”
The ad says“Experience with Agile and Test-Driven Development methodology.”
The ad says“Hands-on experience in a Unix/Linux environment.”

It's fun to work in a company where people truly BELIEVE in what they are doing!

We're committed to bringing passion and customer focus to the business.

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.

Please visit Fractal | Intelligence for Imagination for more information about Fractal

Note: This position is not eligible for Immigration Sponsorship at this time

Location: Bay Area, CA (Hybrid, 3 days per week onsite)

Role Overview:

One of our well-known clients, a leading global digital retail and e-commerce organization, is seeking a Senior Data Engineer to design, build, and operate large-scale, production-grade data platforms that power analytics and data science across the Retail Online organization.

This is a senior, hands-on engineering role for someone who can operate at the intersection of data pipeline architecture, analytics engineering, and production operations. The person will partner with Data Science, Analytics, and Business teams to scope initiatives, govern cross-functional dependencies, and deliver dependable, production-grade data assets that serve analysts, data scientists, and decision-makers.

The ideal candidate is not just a strong technologist. They are a delivery-minded engineer who can manage cross-functional programs, enforce rigorous QA and observability standards, translate complex methodologies into actionable insights, and keep mission-critical pipelines reliable, scalable, and cost-efficient.

Key Responsibilities

Project Management

Cross-Functional Scoping & Dependency Governance — Plan project scope, timelines, and dependencies across Data Science, Analytics, and Business teams. Track critical paths and coordinate deliverables to ensure continuous, seamless delivery.
Stakeholder Alignment & Executive Reporting — Maintain project tracking artifacts and status dashboards. Prepare and deliver executive roadmap updates, milestone progress, and risk mitigation summaries to leadership.

Global Team Coordination & Technical Hand-offs — Direct coordination with offshore engineering teams. Align on technical designs, enforce development standards, and lead structured code and documentation reviews.
Delivery Governance & SLA Accountability — Define delivery milestones, manage scope changes, and enforce operational SLAs. Lead cross-team incident escalations and post-incident reviews to maintain execution quality.

Analytics Execution Management

Analytics QA & Production-Grade Artifact Standards — Develop, validate, and maintain Tableau dashboards and metric logic as tested, version-controlled production software. Enforce strict pre-release QA validation gates to guarantee analytical accuracy.
Statistical Model Validation & Data Science Enablement — Partner with Data Scientists to validate data pipelines supporting forecasting, causal inference, incrementality, and MMM. Ensure inputs are fully reproducible for model development.
Experimentation QA & Feature Store Governance — Oversee QA for A/B testing infrastructure, experiment tracking, feature stores, and inference workflows. Audit tracking mechanisms to ensure consistency between prototype models and production.
Domain Metric Integrity & Strategic Insights Translation — Audit retail customer behavior data transformations against operational logic. Translate complex statistical methodologies into validated, actionable insights for technical and business audiences.

Data Pipeline Management

Production ETL/ELT Architecture & Pipeline Engineering — Design and optimize scalable, automated ETL/ELT pipelines. Deliver dependable, production-grade data assets tailored for analysts, data scientists, and decision-makers.
Proactive Observability & Data Quality Monitoring — Build and maintain monitoring systems to detect pipeline health issues, schema drift, data quality anomalies, and compute cost spikes before end users are impacted.
Containerization, CI/CD & Kubernetes Orchestration — Containerize data applications with Docker and integrate into CI/CD workflows. Deploy, manage, and debug scheduled and streaming workloads on Kubernetes using manifests and Helm charts.
End-to-End Data Operations & Incident Triage — Own job scheduling, run-book maintenance, and incident triage with a support-first mindset. Rapidly resolve pipeline failures and maintain playbooks to secure maximum platform reliability.

Key Qualifications

10+ years of software development and data engineering experience with very high proficiency in Python (production-grade: packaging, testing, CI/CD).
Detailed knowledge of and substantial experience with data structures and algorithms.
Solid technical database knowledge across Hadoop, Python, and Snowflake — data modeling, performance tuning, cost governance, and large-scale query optimization.
Experience working with large-scale data warehouse and data lake solutions such as Teradata, Snowflake, Redshift, and Hadoop/HDFS-based ecosystems.
Hands-on Kubernetes experience — deploying data workloads, managing namespaces, debugging pods/logs/events, and tuning resource requests and limits.
Proficiency with Docker — authoring Dockerfiles, multi-stage builds, container registries, and integrating images into orchestration and CI/CD pipelines.
Experience owning data operations and support — on-call rotations, SLA management, incident response, runbook authorship, and postmortem processes.
Hands-on experience with Tableau (published data sources, extract schedules, performance optimization).
Experience with Continuous Integration & Delivery and automation tools such as Jenkins, Artifactory, and Git.
Hands-on experience in a Unix/Linux environment.
Experience with Agile and Test-Driven Development methodology.
Ability to present complex ideas in a clear, concise way to both technical and non-technical audiences.

Education

BS in Computer Science, Engineering, Mathematics, Statistics, Econometrics, or other quantitative field.
Preferred: MS in Computer Science, Engineering, Statistical Methods, or Machine Learning.

Pay:

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the starting base salary for this role is $130,000, with the potential for a higher base depending on experience, skills, and overall fit for the position. This role is also eligible for a performance-based bonus tied to achieving sales goals related to new client acquisition and project growth.

Benefits:

As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a “free time” PTO policy, allowing you the flexibility to take the time needed for either sick time or vacation.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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