Lead Data Engineer - Technology Data Product

KeyBank • Brooklyn, OH

8d • Hybrid

About The Position

KeyCorp is seeking a Lead Data Engineer to support the design, implementation, maintenance, and lifecycle of enterprise data products, beginning with a DevOps Data Product that transforms technology, operational, and business data into trusted, governed, reusable insights. This hands-on technical leadership role partners with Data Product Owners, data modelers, data architects, platform engineers, technology teams, and business stakeholders to build scalable data pipelines, reusable data models, cloud-native services, and deployment automation on Google Cloud Platform. The role contributes to data engineering standards and platform capabilities, with an emphasis on data quality, reliability, governance, resilience, and efficient delivery.

The position is based at 4910 Tiedeman Road, Brooklyn, Ohio, and is categorized as hybrid, with at least two days in the office. It is eligible for a base salary of $80,000–$150,000 annually, plus eligibility for incentive compensation. Placement in the range may depend on skills, experience, and geographic location. KeyCorp is an Equal Opportunity Employer committed to an inclusive culture.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline, or equivalent practical experience.
• At least 5 years of hands-on data engineering experience building production cloud data pipelines and data warehouse solutions.
• At least 2 years of practical experience integrating automated testing, infrastructure as code, and CI/CD deployment workflows.
• Advanced SQL proficiency and hands-on BigQuery experience, including datasets, partitioning, clustering, views, schema updates, access controls, and query optimization.
• Experience designing and operating production ELT/ETL pipelines, state management, incremental loading, and workflow scheduling with Cloud Composer or Apache Airflow.
• Strong hands-on Python and Bash shell scripting skills for container and pipeline workflows.
• Practical experience ingesting data from enterprise REST or GraphQL APIs, including pagination, rate limits, OAuth flows, and secret-management integration.
• Hands-on experience with Dataform or comparable SQL-based transformation frameworks, including modular transformations, dependencies, and automated test assertions.
• Experience writing reusable Terraform modules to provision GCP data and IAM resources, including BigQuery, Cloud Storage, service accounts, Cloud Run, and Cloud Composer.
• Practical experience maintaining GitLab CI/CD pipelines, including environment stages, automated testing, container builds, and branch management.
• Experience implementing automated data-quality controls, reconciliation, observability, alerting, failure recovery, and production support.
• Experience applying access controls, secure credential handling, lineage, auditability, and data-governance requirements in a regulated or highly governed environment.
• Ability to meet the stated general-office physical demands, including prolonged sitting, communication in person or by phone, frequent PC/laptop use, and occasional handling of bags weighing up to 10 pounds.
• All KeyBank employees are expected to demonstrate Key’s Values and abide by Key’s Code of Conduct.

Nice To Haves

• Experience packaging and running lightweight workloads using Docker, Cloud Build, and Cloud Run.
• Prior experience building reporting data models around software engineering tools such as Jira, ServiceNow, or GitLab.
• Familiarity with event-driven data ingestion using Pub/Sub or Apache Beam / Google Cloud Dataflow.
• Familiarity with engineering, operational, productivity, quality, cost, risk, or AI-related data.

Responsibilities

• Design, build, and support production batch and incremental data pipelines using Python, SQL, and Cloud Composer to collect and process enterprise tool and source-system data and telemetry.
• Implement and maintain BigQuery datasets, tables, views, and transformations; optimize partitioning, clustering, query performance, access, storage, and compute costs.
• Develop and deploy automated data transformations and data-quality checks using Dataform.
• Create and maintain reusable Terraform configurations and GitLab CI/CD pipelines to automate testing, credential handling, and deployments across development, test, and production environments.
• Build secure integrations with enterprise APIs and source systems, including appropriate authentication, credential management, retry, error-handling, and rate-limiting patterns.
• Configure pipeline monitoring, alerting, schema validation, and reconciliation jobs.
• Partner with data product, modeling, architecture, and platform teams to translate product requirements, metric definitions, data-quality expectations, and governance requirements into technical solutions.
• Maintain technical documentation, lineage, data contracts, implementation guides, and evidence supporting governance and audit requirements.
• Conduct code reviews, establish reusable coding templates, and mentor engineers on data engineering and version-control practices.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior