Manager, Dev Ops & Data Engineering

About the Role

Key Responsibilities

• Lead and mentor a team of data and DevOps engineers fostering a culture of growth and excellence.
• Define and execute the technical roadmap for data infrastructure and DevOps practices.
• Build and scale a high-performing team of data engineers to enhance data pipelines, develop new data sources, refine existing datasets, and improve data models as PatientPoint's products evolve.
• Conduct regular performance evaluations, establish individual objectives, and deliver constructive feedback to support professional development.
• Drive team and organizational growth by actively participating in the recruitment and onboarding of top-tier data engineering talent.
• Collaborate with peers, leadership and stakeholders to define project scope, objectives, and deliverables that align with organizational goals.
• Develop and monitor project timelines, ensuring milestones are achieved and deliverables are met on schedule.
• Partner with cross-functional teams to ensure seamless integration of data solutions across the organization.
• Work closely with peers, Data Modeler, QA team in maintaining scalable, reliable, and high-performance data pipelines.
• Own and maintain CI/CD framework along with pipelines for data and application deployments.
• Act as the subject matter expert for the organization’s data platform and pipelines, contributing to their development and strategic direction.
• Oversee the creation of automated data quality assurance processes and operational support strategies to maintain data reliability.

Requirements

• 7+ years of experience in data/DevOps engineering positions.
• 3+ years in a managerial or team leadership role developing data infrastructure and technology systems.
• Experience in Managing cloud data warehousing platforms (Snowflake, Google BigQuery) and ensuring cost efficiency.
• Prior experience in Implementing security best practices for data storage, processing, and access control.
• Significant experience with modern software development practices, including CI/CD, automated testing, and cloud-native architecture.
• Experience in engineering large-scale enterprise applications end-to-end, with a focus on Data Engineering and Insights.
• Proven ability to evaluate the current technology stack and advocate for strategic enhancements to optimize value delivery to the business.
• Experience with working with modern data architecture as well as data transformation tooling.
• Experience with Snowflake or Google Big Query required.
• Strong project management skills, with a track record of delivering complex projects on time and within scope.
• Excellent communication and leadership skills.

Nice to Have

• BA/BS in Computer Science, Computer Engineering, Information Technology, Management Information Systems, Software Engineering, Software Development, Data Engineering or related field.
• Experience with collaboration tools (Teams, Slack, Jira, Confluence).
• Prior experience in designing and implementing Snowflake Rules Based Architecture (RBAC).
• Experience in managing SOWs and vendor contracts.
• Experience with dbt.
• Experience with Data Management and Data quality concepts.
• Experience with Terraform.
• Expertise in common programming/code languages, orchestration and tooling, such as SQL, Python, Airflow, etc.

Qualifications

• BA/BS in relevant field (preferred but not mandatory).

Benefits & Perks

• Competitive compensation.
• Flexible time off to recharge.
• Hybrid work options.
• Mental and emotional wellness resources.
• A 401K plan.
• Supportive environment with modernized benefits and cultural perks.