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The Senior Manager, Data Engineering leads a team of data engineers responsible for designing, building, and operating the scalable data pipelines, architectures, and platforms that power AssistRx’s data-driven initiatives. This role blends hands-on technical leadership with people management, owning delivery across multiple concurrent client implementations and internal data programs. Partnering closely with product, analytics, engineering, and business stakeholders, the Senior Manager translates strategic priorities into executable engineering roadmaps, develops talent, and ensures the team consistently delivers reliable, high-quality, and compliant data solutions. This role is accountable for both the technical health of the data platform and the growth and performance of the engineering team. Team Leadership & People Management •     Lead, mentor, and develop a team of data engineers, setting clear goals, expectations, and growth plans. •     Conduct performance reviews, provide ongoing coaching, and support career development across the team. •     Manage resourcing, capacity planning, and workload balancing across multiple projects and clients. •     Foster a collaborative, inclusive, and high-performing engineering culture. Delivery & Execution Management •     Own end-to-end delivery of data engineering initiatives, ensuring quality, timeliness, and alignment with business goals. •     Plan, prioritize, and track team workstreams across client onboarding, migrations, and platform enhancements. •     Remove blockers, manage risks and dependencies, and escalate issues appropriately to leadership. •     Partner with project and program managers to set realistic timelines and commitments. Technical Oversight & Architecture •     Provide technical direction for ETL/ELT development using Azure Data Factory, dbt, Snowflake, Salesforce, and related platforms. •     Review and guide data architecture, models, warehouses, data lakes, and data vault designs for scalability and maintainability. •     Ensure adoption of engineering best practices for integration, transformation, testing, and deployment. •     Make build-versus-buy and tooling recommendations in partnership with the Director. Data Quality, Governance & Compliance •     Ensure robust data quality frameworks, validation, and monitoring are implemented across pipelines. •     Uphold data accuracy, integrity, security, and compliance, including PHI/PII considerations. •     Establish standards and documentation for data flows, architecture, and transformations. •     Drive resolution of performance, reliability, and cost-efficiency issues across the platform. Stakeholder Engagement & Collaboration •     Partner with BI, analytics, product, and business teams to align data solutions with reporting and consumption needs. •     Communicate progress, risks, and technical concepts clearly to both technical and non-technical stakeholders. •     Contribute to roadmap planning and prioritization of data initiatives across the organization. Continuous Improvement & Innovation •     Identify and implement improvements to engineering processes, automation, and operational efficiency. •     Evaluate emerging tools, technologies, and frameworks to advance team capability. •     Stay current with industry trends in data engineering, cloud platforms, and big data technologies. Additional Responsibilities •     Perform