Job description

Build the data foundation that powers Gallup’s products, analytics and AI innovation. As a senior data engineer at Gallup, you’ll design and build the production data systems that enable high-quality, analytics-ready data across our product and research teams. You’ll translate architectural vision into scalable pipelines, resilient data models and reliable operational workflows, helping Gallup modernize legacy systems and accelerate our AI ambitions. What You’ll Do Design and implement reliable, scalable data pipelines that ingest, process and serve structured and unstructured data across Gallup Build transformation pipelines that convert raw data into high-quality datasets for analytics and experimentation Implement layered data models (raw → curated → semantic) to support analytics, experimentation and AI/ML workflows, with attention to reproducibility and data lineage Translate architectural patterns into production-grade pipelines, models and infrastructure Design systems for reliability, scalability and maintainability in complex, evolving environments Implement monitoring, alerting and automated data quality checks to improve reliability and observability Support incident response, root cause analysis and operational improvements Establish and contribute to standards for data modeling, pipeline design and operational workflows Work closely with product managers, analysts, data scientists and software engineers to understand data needs and build scalable solutions Help teams transition from manual and legacy workflows to automated, modern data systems Mentor engineers through code reviews and architectural discussions What Makes You Stand Out Execution excellence: You have built and operated production data systems and understand the realities of running pipelines reliably at scale. Practical problem solver: You bring sound engineering judgment to incomplete documentation, legacy workflows and evolving requirements. You make thoughtful tradeoffs and sequence work intelligently. Modern data builder: You are fluent in ingestion frameworks, transformation pipelines and layered data modeling, and you translate architectural direction into clean, production-grade implementations. Collaborative partner: You enjoy working across product, analytics and engineering teams and can translate business needs into scalable technical capabilities. AI-forward mindset: You are curious about AI and modern tooling, experiment beyond your day job, and think intentionally about how data modeling and accessibility support AI systems and reproducibility. What You Need Bachelor’s or master’s degree in computer science, engineering or a related field, or equivalent experience required At least five years of experience in data engineering or backend engineering focused on data systems required Strong SQL skills and deep understanding of data modeling required Experience designing and operating production data pipelines required Experience with orchestration tools such as Airflow or Dagster required Experience running dbt workflows or similar transformation frameworks required Hands-on experience with cloud data platforms such as Snowflake, Databricks or BigQuery required Strong programming experience in Python or similar languages required Experience implementing data quality, monitoring or observability frameworks required Experience leading or participating in data platform modernization or migration from legacy environments strongly preferred Experience with AWS preferred Experience partnering directly with nontechnical stakeholders and influencing business decisions from a technical lens preferred Experience working closely with AI teams in environments where data quality and reproducibility are critical preferred A commitment to working on-site at Gallup’s San Francisco office at least three days per week required About Gallup At Gallup, we change the world, one client at a time, through extraordinary analytics and advice on everything important facing humankind. Learn more about our work and life at Gallup . Gallup offers a robust benefits package that includes medical, dental, vision, life and other insurance options; a fully vested 401(k) retirement savings plan with company matching; an employee stock ownership program; mass transit reimbursement; family-building benefits; an employee assistance program; and various reimbursements and activities that enhance our associates’ wellbeing. We also offer an estimated annual salary range of $220,000-$260,000 for this role. Salaries are based on a variety of factors, including an individual’s education, experience and skills. Gallup is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender identity, or any other legally protected basis, in accordance with applicable law. To review Gallup’s Privacy Statement, please click this link: gallup.com . This privacy policy is meant to help you understand what information we collect, why we collect it, and how you can update, manage and delete your information. Your application and the information you provide will be processed and stored in the United States. #LI-Hybrid #LI-KW1

Requirements

Must-haves

Build the data foundation that powers Gallup’s products, analytics and AI innovation.
What You’ll Do
Design and implement reliable, scalable data pipelines that ingest, process and serve structured and unstructured data across Gallup
Build transformation pipelines that convert raw data into high-quality datasets for analytics and experimentation
Implement layered data models (raw → curated → semantic) to support analytics, experimentation and AI/ML workflows, with attention to reproducibility and data lineage
Translate architectural patterns into production-grade pipelines, models and infrastructure
Design systems for reliability, scalability and maintainability in complex, evolving environments
Implement monitoring, alerting and automated data quality checks to improve reliability and observability
Support incident response, root cause analysis and operational improvements
Establish and contribute to standards for data modeling, pipeline design and operational workflows
Work closely with product managers, analysts, data scientists and software engineers to understand data needs and build scalable solutions
Help teams transition from manual and legacy workflows to automated, modern data systems
Mentor engineers through code reviews and architectural discussions
What Makes You Stand Out
Execution excellence: You have built and operated production data systems and understand the realities of running pipelines reliably at scale.
Practical problem solver: You bring sound engineering judgment to incomplete documentation, legacy workflows and evolving requirements. You make thoughtful tradeoffs and sequence work intelligently.
Modern data builder: You are fluent in ingestion frameworks, transformation pipelines and layered data modeling, and you translate architectural direction into clean, production-grade implementations.
Collaborative partner: You enjoy working across product, analytics and engineering teams and can translate business needs into scalable technical capabilities.
AI-forward mindset: You are curious about AI and modern tooling, experiment beyond your day job, and think intentionally about how data modeling and accessibility support AI systems and reproducibility.
What You Need

Nice-to-haves

Experience leading or participating in data platform modernization or migration from legacy environments strongly preferred
Experience with AWS preferred
Experience partnering directly with nontechnical stakeholders and influencing business decisions from a technical lens preferred
Experience working closely with AI teams in environments where data quality and reproducibility are critical preferred

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aimldesign systemsaccessibilitysqlpythonaws

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Benefits

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Dental

Vision

401(K)