Manager, Data Platform – Engineering

TheKey

Manager, Data Platform & Engineering at TheKey overseeing AI-ready data initiatives. Building scalable data pipelines and leading a team of data engineers in a hybrid remote environment.

Posted 4/23/2026full-timeRemote • Texas • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

BigQueryCloudETL

About the role

Key responsibilities & impact

Contribute to and execute a roadmap that positions TheKey's data platform as AI-ready — well-structured, richly documented, and accessible for machine learning and generative AI use cases.
Champion the adoption of AI and automation tools within the data engineering team to increase delivery velocity and reduce manual effort.
Partner with business and technology stakeholders to align platform capabilities with analytics and AI initiatives.
Lead the design and governance of a metadata-rich data lake in Google BigQuery, ensuring datasets are tagged, documented, and contextualized.
Establish and enforce standards for data cataloging, semantic tagging, lineage tracking, and business glossary definitions.
Drive adoption of tools such as Google Dataplex or equivalent for automated metadata management and data quality enforcement.
Build and maintain scalable data pipelines, leveraging AI-assisted development tools to accelerate development and reduce errors.
Implement AI-driven testing and observability frameworks to automatically validate pipeline outputs, detect anomalies, and enforce data quality.
Define and enforce data governance frameworks that support both regulatory compliance and AI readiness.
Own master data management practices to ensure accuracy, consistency, and a single source of truth for critical business entities.
Directly manage a team of data engineers – providing mentorship, clear expectations, and career development support.

Requirements

What you’ll need

Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field.
5+ years of experience in data engineering, with at least 1–2 years in a team lead or people management capacity.
Hands-on expertise with Google BigQuery and the broader Google Cloud data ecosystem (Dataflow, Pub/Sub, Dataplex, Looker, etc.).
Demonstrated experience building and managing cloud-native data pipelines and ELT/ETL processes at scale.
Working knowledge of AI/ML workflows and what it takes to prepare data for model training, RAG pipelines, or AI-powered analytics.
Experience implementing data catalogs, metadata frameworks, and data lineage tooling.
Familiarity with AI-assisted development tools and a track record of integrating them into engineering workflows.
Strong data governance background including security, compliance, and quality frameworks.
Strong communication and stakeholder management skills.

Benefits

Comp & perks

Medical/Dental/Vision Insurance
TouchCare VirtualCare
Life Insurance
Health Savings Account
Flexible Spending Account
401(k) Matching
Employee Assistance Program
PTO Plan for Non-Exempt Employees
Flexible PTO Plan for Exempt Employees
Holidays and Floating Holidays
Pet Insurance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringmetadata managementdata governancecloud-native data pipelinesELT processesETL processesAI/ML workflowsdata catalogingsemantic taggingdata lineage

Soft Skills

team leadershipmentorshipstakeholder managementcommunicationcareer development support

Certifications

Bachelor's degree in Computer ScienceMaster's degree in Computer ScienceBachelor's degree in Information SystemsMaster's degree in Information SystemsBachelor's degree in Data EngineeringMaster's degree in Data Engineering