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# Manager, Data Engineering

- **Company:** Fuze
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $180,000.0 - $225,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Database, Computer Programming, Computer Terminals, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Warehousing, Python (Programming Language), Machine Learning, Operational Databases, Standard Sql, Usage Analysis, Cloud Platform System, Feature Engineering, Data Ingestion, System Availability, Delivery Pipeline, Snowflake, Data Lineage, Apache Kafka, Data Management, Machine Learning Operations, Stream Analytics, Looker Analytics, Data Pipelines
- **Published:** September 5, 2026
- **Apply:** https://startup.jobs/senior-manager-data-engineering-alto-pharmacy-company-9851879

## About the Role

* Bachelor's degree in Computer Science, Engineering, Mathematics, or related field; advanced degree preferred.
 * 10+ years of experience in data engineering, platform engineering, or related data infrastructure roles.
 * 5+ years of experience leading and scaling high-performing technical teams.
 * Proven experience architecting, operating, and scaling modern cloud-based data platforms, including data ingestion, orchestration, cloud data warehouses, transformation frameworks, and semantic serving layers.
 * Strong expertise in data modeling principles, ELT architectures, and production-grade pipeline orchestration.
 * Hands-on experience with cloud environments (AWS, GCP, or Azure).
 * Proven track record owning platform reliability, including defining SLAs, implementing observability and data quality frameworks, and leading incident response and postmortems for production data systems.
 * Experience operating in high-growth, fast-paced technology organizations.
 * Strong communication skills with the ability to influence technical and non-technical stakeholders alike., * Experience building data platforms in healthcare, pharmacy, fintech, or other regulated industries.
 * Familiarity with HIPAA and healthcare data privacy standards.
 * Experience supporting machine learning pipelines, feature engineering workflows, or feature stores.
 * Experience with streaming architectures (e.g., Kafka, Kinesis, Pub/Sub) and real-time analytics use cases.
 * Exposure to experimentation platforms and product analytics ecosystems.
 * Strong SQL and programming proficiency (e.g., Python, Scala, or similar).
 * Experience implementing data contracts and data product frameworks across domain teams., Physical requirements for this role include the ability to work at a computer terminal with monitor, keyboard and mouse for extended periods of time, stoop, bend, and reach for equipment and supplies, make frequent repetitive motions required to operate a computer that include the wrists, hands and fingers, and lift, carry, push, pull, and move light objects up to 20 pounds. The role also requires the ability to effectively communicate through verbal interactions, discern auditory information, and visually perceive details to perform essential job functions.

## Description

At Alto, we are transforming the pharmacy experience through intelligent, scalable technology. Data is foundational to how we serve patients, empower operators, and enable smarter decision-making across the business. As the Senior Manager, Data Engineering, you will lead the strategy, architecture, and execution of Alto's data platform - ensuring that high-quality, trusted, and timely data fuels everything from analytics and operations to product innovation and machine learning.
You will manage, build and lead a high-performing team responsible for designing resilient data pipelines, evolving our modern data stack, and establishing data engineering best practices. This role is equal parts technical leadership, organizational design, and cross-functional partnership - shaping how data is produced, governed, and consumed across a fast-growing, technology-driven healthcare organization., Leadership & Vision

 * Lead, mentor, and grow a team of Data Engineers, fostering a culture of ownership, technical excellence, and continuous improvement.
 * Define and execute the long-term vision for Alto's data platform, ensuring alignment with company strategy and product roadmaps.
 * Partner with Product, Engineering, Data Science, Analytics, Finance, and Enterprise teams to prioritize and deliver high-impact data initiatives.
 * Establish clear career paths, performance standards, and hiring plans to scale the team thoughtfully and sustainably.
 * Build strong stakeholder trust by translating business needs into scalable data solutions.

Data Platform & Architecture

 * Own the design and evolution of Alto's data architecture, including ingestion, transformation, orchestration, storage, and serving layers.
 * Administer and maintain core platform tooling - including Fivetran, Airflow, dbt, Snowflake, and Looker - ensuring these systems operate as reliable, scalable, and secure infrastructure.
 * Provide a robust, well-governed platform foundation that enables Analytics to build and manage transformation logic within dbt, while enforcing standards for performance, testing, deployment workflows, access controls, and warehouse efficiency.
 * Ensure the underlying data platform reliably powers analytics, operational workflows, experimentation, and machine learning use cases - delivering trusted, well-documented, and production-grade data assets to both internal stakeholders and downstream systems.
 * Ensure the reliability, performance, and freshness of data pipelines through strong observability, lineage tracking, testing frameworks, and operational rigor.
 * Scale the platform to support increasing data volume, near-real-time use cases, and expanding business and regulatory complexity.

Data Governance, Quality & Operational Excellence

 * Evolve and strengthen existing standards for data governance, access control, privacy, and compliance within a regulated healthcare environment.
 * Refine and operationalize SLAs and performance metrics for data pipelines and platform reliability, ensuring clear accountability and transparency.
 * Enhance and scale current data quality monitoring and incident management practices to improve resilience, observability, and response times.
 * Continuously optimize infrastructure performance and cost efficiency through thoughtful architectural improvements and warehouse tuning.

Innovation & Cross-Functional Impact

 * Evaluate emerging technologies and evolve Alto's data stack to support streaming, near-real-time analytics, and scalable AI workflows.
 * Enable robust experimentation and measurement by providing reliable, well-instrumented, and production-grade data pipelines that Analytics, Data Science, and Product teams can confidently build upon.
 * Collaborate closely with Data Science and Machine Learning teams to ensure the platform scales alongside growing model and feature complexity, providing the infrastructure, environment consistency, and operational guardrails necessary for reliable training and production inference.
 * Drive adoption of best-in-class tooling and practices that improve developer velocity and reduce operational toil.
 * Cultivate a culture where data is treated as a product - with clear ownership, discoverability, and accountability.


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