This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Manager, Data Platform Engineering based in the United States.
This is a senior engineering leadership role responsible for scaling a modern data platform and the team behind it.
You will combine people leadership, technical judgment, and execution discipline to deliver reliable, high-impact data capabilities.
The role partners closely with Product, Engineering, Architecture, Client Delivery, Operations, and business stakeholders.
You will guide complex initiatives from planning through production while improving delivery predictability, technical quality, and operational resilience.
Your work will shape scalable data ingestion, transformation, lakehouse architecture, governance, and reusable platform capabilities.
The position also plays a key role in strengthening engineering practices around observability, data quality, incident management, and on-call readiness.
This is an opportunity to lead a growing team while building foundational technology that supports analytics, applications, and business growth.
Accountabilities:
- Lead, coach, and develop a high-performing Data Platform engineering team through clear expectations, career development, regular feedback, performance management, and strong technical leadership.
- Own execution of complex data initiatives, translating strategic priorities into realistic delivery plans with defined scope, milestones, owners, dependencies, capacity assumptions, risks, decisions, and target dates.
- Establish disciplined delivery practices by ensuring initiatives are technically understood, appropriately estimated, sequenced, and ready before commitments are made.
- Maintain accountability throughout delivery, proactively addressing blockers, dependencies, scope changes, capacity constraints, and technical risks, with early escalation and mitigation when commitments are threatened.
- Maintain sufficient technical depth to independently evaluate implementation and delivery risks while partnering with Staff Engineers and other technical leaders on architecture, estimates, technical readiness, root-cause analysis, and quality.
- Build trusted relationships across Product, Client Delivery, Engineering, Architecture, Operations, and other business functions to align priorities, resolve tradeoffs, and communicate clear, fact-based decisions and status updates.
- Drive operational excellence across production support, on-call readiness, incident management, data quality, observability, backup coverage, escalation processes, and follow-through on corrective actions.
- Guide the evolution of scalable data ingestion, ETL/ELT, distributed processing, lakehouse and cloud architecture, governance, and reusable platform capabilities.
- Establish and continuously improve engineering standards, operational practices, and platform architecture to support long-term scalability, maintainability, and reliability.
- Support the team through periods of significant growth by strengthening delivery practices, technical standards, operational discipline, and platform capabilities.
Requirements
- 8+ years of experience in data engineering, platform engineering, software engineering, or a related technical discipline, including at least 3 years of direct people management within a production engineering environment.
- Demonstrated success building, coaching, and managing high-performing engineering teams, including setting expectations, developing talent, managing performance, and creating accountability for outcomes.
- Proven experience leading complex, cross-functional engineering initiatives from planning through production, with strong capabilities in delivery management, dependency tracking, risk mitigation, and improving predictability.
- Strong technical depth across modern data platforms, including data ingestion, ETL/ELT, distributed data processing, data modeling, cloud-based data architecture, and production data systems.
- Hands-on experience with modern cloud and data technologies such as AWS, S3, Iceberg, Glue, Airflow, Spark/PySpark, Athena, or comparable technologies.
- Strong understanding of engineering quality and operational practices, including testing, data quality, observability, incident management, on-call operations, version control, CI/CD, and production reliability.
- Excellent written and verbal communication skills, with the ability to provide concise, accurate updates to senior leaders and effectively navigate priorities, tradeoffs, risks, and decisions across technical and non-technical stakeholders.
- Experience building or operating enterprise-scale data lakehouse, data platform, or data infrastructure capabilities is highly valued.
- Experience working with healthcare data such as claims, eligibility, clinical, provider, or other regulated datasets is preferred.
- Familiarity with data governance, metadata management, data cataloging, security, privacy, and regulated data environments is advantageous.
- Demonstrated ability to operate successfully during periods of rapid organizational and technical growth.
- Strong leadership presence, collaboration skills, accountability, and ability to balance strategic thinking with hands-on technical judgment.
Benefits
- Salary: Annual base salary of $175,000–$195,000, with individual compensation determined by qualifications, experience, skill set, and internal alignment.
- Bonus: Total compensation package includes eligibility for a bonus.
- Remote work: Fully remote opportunity with approximately 5% travel.
- Healthcare: Medical, dental, and vision insurance.
- Financial wellness: 401(k) retirement plan with company match, plus flexible spending and health savings account options.
- Insurance: Life and disability insurance coverage.
- Time off: Flexible Time Off and company holidays.
- Parental leave: Up to 14 weeks of paid parental leave.
- Pet benefits: Pet insurance.
- Employee support: Employee Assistance Program.
- Career growth: Opportunity to lead a growing engineering organization and influence the evolution of enterprise-scale data infrastructure.
- Collaboration: Work alongside Product, Engineering, Architecture, Client Delivery, and business teams on high-impact data initiatives.
- Work environment: Supportive, growth-oriented culture emphasizing empathy, candid collaboration, accountability, and inclusive teamwork.
- Travel: Occasional travel to Boston, MA may be required for onboarding and periodic in-person team meetings.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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