Mid Level Lead Product Owner Jobs
Mid level lead product owner jobs go to professionals ready to own product features end to end, guide junior teammates, and drive roadmap decisions without close supervision. Openings are spread across on-site, remote, and hybrid settings in Technology & Software, Banking & Financial Services, and Investment & Asset Management, with employers like TikTok, Google, and Corpay hiring at this level now.
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Showing 5 of 63+ Mid Level Lead Product Owner jobs
Location:
4910 Tiedeman Road, Brooklyn Ohio
Job Summary
We are seeking a Lead Data Engineer to support the design, implementation, maintenance, and lifecycle of enterprise data products starting with our DevOps Data Product transforming technology, operational, and business data into trusted, governed, and reusable insights.
In this hands-on technical leadership role, you will partner with Data Product Owners, data modelers, data architects, platform engineers, technology teams, and business stakeholders to develop scalable data pipelines, reusable data models, cloud-native services, and deployment automation on Google Cloud Platform.
This is a strong fit for someone who enjoys solving complex data and platform problems, improving data quality and reliability, reducing friction in the data delivery and pipeline lifecycle, and building standardized solutions that encourage broad adoption. The role offers the opportunity to influence data engineering standards, strengthen platform capabilities, and help shape a delivery ecosystem built for speed, quality, governance, and resilience.
Essential Functions
- Data Pipeline Engineering: Design, build, and support production batch and incremental pipelines using Python, SQL, and Cloud Composer to collect and process data and telemetry from enterprise tools and source systems.
- BigQuery Engineering & Optimization: Implement and maintain BigQuery datasets, tables, views, and transformation workloads. Optimize partitioning, clustering, query performance, access, storage, and compute costs.
- Data Transformation & Testing: Write and deploy automated transformation workflows and data quality checks using Dataform.
- CI/CD & Infrastructure as Code: Create and maintain repeatable Terraform configurations and GitLab CI/CD pipelines to automate testing, credential handling, and environment deployments across development, test, and production.
- System Integration & Security: Build secure integrations with enterprise APIs and source systems using appropriate authentication and credential management, incorporating retry, error handling, and rate-limiting patterns.
- Data Quality & Reliability: Configure pipeline monitoring, alerting, schema validation, and reconciliation jobs.
- Data Product Delivery: Partner with the Data Product Owner, data modelers, architects, and platform teams to translate product requirements, metric definitions, data-quality expectations, and governance requirements into reliable technical solutions.
- Documentation & Governance: Maintain technical documentation, lineage, data contracts, implementation guides, and evidence needed to support governance and audit requirements.
- Technical Mentorship & Standards: Conduct code reviews, establish reusable coding templates, and mentor team engineers on best practices for data engineering and version control.
Required Technical Skills
- SQL & BigQuery: Advanced SQL proficiency with hands-on BigQuery experience managing datasets, partitioning, clustering, views, schema updates, access controls, and query optimization.
- Data Pipeline & Orchestration: Proven experience designing and running production ELT/ETL pipelines, state management, incremental loading, and workflow scheduling with Cloud Composer or Apache Airflow.
- Programming & Scripting: Strong hands-on programming skills in Python and Bash shell scripting for container and pipeline workflows.
- API Ingestion: Practical experience extracting data from enterprise REST or GraphQL APIs, handling pagination, rate limits, OAuth flows, and integration with secret management systems.
- Dataform / SQL Transformation: Hands-on experience developing modular data transformations, dependencies, and automated test assertions using Dataform or comparable SQL-based frameworks.
- Terraform & GCP Infrastructure: Experience writing reusable Terraform modules to provision GCP data and IAM resources, including BigQuery, Cloud Storage, service accounts, Cloud Run, and Cloud Composer.
- GitLab CI/CD: Practical experience maintaining GitLab CI/CD pipelines, including environment stages, automated testing, container builds, and branch management.
- Data Quality & Production Reliability: Experience implementing automated data-quality controls, reconciliation, observability, alerting, failure recovery, and production support.
- Security & Governance: Experience applying access controls, secure credential handling, lineage, auditability, and data-governance requirements within a regulated or highly governed environment.
Preferred Technical Skills
- Containerization: Experience packaging and running lightweight workloads using Docker, Cloud Build, and Cloud Run.
- Developer Telemetry: Prior experience building reporting data models around software engineering tools, such as Jira, ServiceNow, GitLab.
- Streaming & Event Ingestion: Familiarity with event-driven data ingestion using Pub/Sub or Apache Beam / Google Cloud Dataflow.
- Analytics & AI Readiness: Familiarity with engineering, operational, productivity, quality, cost, risk, or AI-related data.
Work Experience & Education
- Education: Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline, or equivalent practical experience.
- Relevant Experience: 5+ years of hands-on data engineering experience building production cloud data pipelines and data warehouse solutions.
- DevOps / CI/CD Experience: 2+ years of practical experience integrating automated testing, infrastructure as code, and CI/CD deployment workflows.
Core Competencies
- All KeyBank employees are expected to demonstrate Key’s Values and abide by Key’s Code of Conduct.
Physical Demands
- General Office - Prolonged sitting, ability to communicate face to face in person or on the phone with teammates and clients, frequent use of PC/laptop, occasional lifting/pushing/pulling of backpacks, computer bags up to 10 lbs.
Work Location Category
- Hybrid (2+ days)
COMPENSATION AND BENEFITS
This position is eligible to earn a base salary in the range of $80,000.00 - $150,000.00 annually. Placement within the pay range may differ based upon various factors, including but not limited to skills, experience and geographic location. Compensation for this role also includes eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.Please click here for a list of benefits for which this position is eligible.
Key has implemented an approach to employee workspaces which prioritizes in-office presence, while providing flexible options in circumstances where roles can be performed effectively in a mobile environment.
Job Posting Expiration Date: 11/18/2026 KeyCorp is an Equal Opportunity Employer committed to sustaining an inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, pregnancy, disability, veteran status or any other characteristic protected by law.Qualified individuals with disabilities or disabled veterans who are unable or limited in their ability to apply on this site may request reasonable accommodations by emailing HR_Compliance@keybank.com.
#LI-Hybrid
Location:
4910 Tiedeman Road, Brooklyn Ohio
Job Summary
We are seeking a Lead Data Engineer to support the design, implementation, maintenance, and lifecycle of enterprise data products starting with our DevOps Data Product transforming technology, operational, and business data into trusted, governed, and reusable insights.
In this hands-on technical leadership role, you will partner with Data Product Owners, data modelers, data architects, platform engineers, technology teams, and business stakeholders to develop scalable data pipelines, reusable data models, cloud-native services, and deployment automation on Google Cloud Platform.
This is a strong fit for someone who enjoys solving complex data and platform problems, improving data quality and reliability, reducing friction in the data delivery and pipeline lifecycle, and building standardized solutions that encourage broad adoption. The role offers the opportunity to influence data engineering standards, strengthen platform capabilities, and help shape a delivery ecosystem built for speed, quality, governance, and resilience.
Essential Functions
- Data Pipeline Engineering: Design, build, and support production batch and incremental pipelines using Python, SQL, and Cloud Composer to collect and process data and telemetry from enterprise tools and source systems.
- BigQuery Engineering & Optimization: Implement and maintain BigQuery datasets, tables, views, and transformation workloads. Optimize partitioning, clustering, query performance, access, storage, and compute costs.
- Data Transformation & Testing: Write and deploy automated transformation workflows and data quality checks using Dataform.
- CI/CD & Infrastructure as Code: Create and maintain repeatable Terraform configurations and GitLab CI/CD pipelines to automate testing, credential handling, and environment deployments across development, test, and production.
- System Integration & Security: Build secure integrations with enterprise APIs and source systems using appropriate authentication and credential management, incorporating retry, error handling, and rate-limiting patterns.
- Data Quality & Reliability: Configure pipeline monitoring, alerting, schema validation, and reconciliation jobs.
- Data Product Delivery: Partner with the Data Product Owner, data modelers, architects, and platform teams to translate product requirements, metric definitions, data-quality expectations, and governance requirements into reliable technical solutions.
- Documentation & Governance: Maintain technical documentation, lineage, data contracts, implementation guides, and evidence needed to support governance and audit requirements.
- Technical Mentorship & Standards: Conduct code reviews, establish reusable coding templates, and mentor team engineers on best practices for data engineering and version control.
Required Technical Skills
- SQL & BigQuery: Advanced SQL proficiency with hands-on BigQuery experience managing datasets, partitioning, clustering, views, schema updates, access controls, and query optimization.
- Data Pipeline & Orchestration: Proven experience designing and running production ELT/ETL pipelines, state management, incremental loading, and workflow scheduling with Cloud Composer or Apache Airflow.
- Programming & Scripting: Strong hands-on programming skills in Python and Bash shell scripting for container and pipeline workflows.
- API Ingestion: Practical experience extracting data from enterprise REST or GraphQL APIs, handling pagination, rate limits, OAuth flows, and integration with secret management systems.
- Dataform / SQL Transformation: Hands-on experience developing modular data transformations, dependencies, and automated test assertions using Dataform or comparable SQL-based frameworks.
- Terraform & GCP Infrastructure: Experience writing reusable Terraform modules to provision GCP data and IAM resources, including BigQuery, Cloud Storage, service accounts, Cloud Run, and Cloud Composer.
- GitLab CI/CD: Practical experience maintaining GitLab CI/CD pipelines, including environment stages, automated testing, container builds, and branch management.
- Data Quality & Production Reliability: Experience implementing automated data-quality controls, reconciliation, observability, alerting, failure recovery, and production support.
- Security & Governance: Experience applying access controls, secure credential handling, lineage, auditability, and data-governance requirements within a regulated or highly governed environment.
Preferred Technical Skills
- Containerization: Experience packaging and running lightweight workloads using Docker, Cloud Build, and Cloud Run.
- Developer Telemetry: Prior experience building reporting data models around software engineering tools, such as Jira, ServiceNow, GitLab.
- Streaming & Event Ingestion: Familiarity with event-driven data ingestion using Pub/Sub or Apache Beam / Google Cloud Dataflow.
- Analytics & AI Readiness: Familiarity with engineering, operational, productivity, quality, cost, risk, or AI-related data.
Work Experience & Education
- Education: Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline, or equivalent practical experience.
- Relevant Experience: 5+ years of hands-on data engineering experience building production cloud data pipelines and data warehouse solutions.
- DevOps / CI/CD Experience: 2+ years of practical experience integrating automated testing, infrastructure as code, and CI/CD deployment workflows.
Core Competencies
- All KeyBank employees are expected to demonstrate Key’s Values and abide by Key’s Code of Conduct.
Physical Demands
- General Office - Prolonged sitting, ability to communicate face to face in person or on the phone with teammates and clients, frequent use of PC/laptop, occasional lifting/pushing/pulling of backpacks, computer bags up to 10 lbs.
Work Location Category
- Hybrid (2+ days)
COMPENSATION AND BENEFITS
This position is eligible to earn a base salary in the range of $80,000.00 - $150,000.00 annually. Placement within the pay range may differ based upon various factors, including but not limited to skills, experience and geographic location. Compensation for this role also includes eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.Please click here for a list of benefits for which this position is eligible.
Key has implemented an approach to employee workspaces which prioritizes in-office presence, while providing flexible options in circumstances where roles can be performed effectively in a mobile environment.
Job Posting Expiration Date: 11/18/2026 KeyCorp is an Equal Opportunity Employer committed to sustaining an inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, pregnancy, disability, veteran status or any other characteristic protected by law.Qualified individuals with disabilities or disabled veterans who are unable or limited in their ability to apply on this site may request reasonable accommodations by emailing HR_Compliance@keybank.com.
#LI-Hybrid
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Find JobsMid Level Lead Product Owner Job Market
Who's Hiring
- TikTok11
- Google3
- Corpay2
- JPMorganChase2
- ENFOS1
Top Industries Hiring
- Technology & Software30
- Banking & Financial Services7
- Investment & Asset Management3
- Fintech2
- Insurance2
Mid Level Lead Product Owner Jobs: Frequently Asked Questions
How do I get a mid level lead product owner job?
Position yourself around ownership, not just contribution. Highlight features or initiatives you led from discovery through delivery, decisions you made without being directed, and any mentoring of junior teammates or stakeholders you aligned. Tailor your resume to show measurable outcomes on the products you touched, and make it clear you can operate independently rather than waiting for direction.
Which companies hire mid level lead product owners?
Companies hiring mid level lead product owners right now include TikTok, Google, and Corpay, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a wide range of employers, from growth-stage technology companies scaling their product teams to large enterprises backfilling roles as senior staff move into director-level positions.
Are there remote mid level lead product owner jobs?
Yes, remote and hybrid options are well represented at this experience level. About 38% of mid level lead product owner openings are remote or hybrid as of November 2026, reflecting how broadly companies have accepted distributed product work. Fully remote roles do exist, though some employers at this level prefer hybrid arrangements to keep leads close to engineering and design teams.
How do I move up to a mid level lead product owner role?
Moving from entry level into mid level means building a record of full-cycle ownership rather than task completion. Focus on taking a feature or initiative all the way from problem definition to launch, documenting the decisions you made and the results they produced. Deepening your fluency in prioritization frameworks, stakeholder communication, and cross-functional alignment over your first few years signals readiness for a lead designation at the mid level.
Which industries hire the most mid level lead product owners?
Mid Level lead product owner roles concentrate in Technology & Software, Banking & Financial Services, and Investment & Asset Management, based on current listings on Migrate Mate as of November 2026. These sectors tend to run large, complex product portfolios that require experienced owners who can manage scope and decisions independently without the overhead of senior or director-level oversight on every initiative.