• 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. • 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. • 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. • 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. • 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. • 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. • Perform other related duties as assigned by leadership. • Directly manages a team of data engineers, including hiring, performance management, and professional development. • Provides technical and career mentorship and leads cross-functional engineering workstreams.

• Build and own Sardine’s internal data infrastructure, integrating CRM, marketing, product, finance, and operational systems into a cohesive, well-modeled data warehouse. • Own the data warehouse partitioning strategy, access controls, and security architecture in close partnership with the Security and Infrastructure teams to meet compliance and performance requirements. • Take full ownership of billing data infrastructure, including backend warehouse tables, data models, and ongoing maintenance. • Design, implement, and own ETL/ELT pipelines to pull and merge data from multiple internal and external systems, ensuring clean, reliable, and scalable data flows across the organization. • Partner with data science, engineering, revenue operations, and executive stakeholders to define and track KPIs, ensuring business decisions are grounded in data. • Serve as the connective tissue between Revenue Operations, Business Operations, and Product/Eng, translating complex requirements into elegant data solutions. • Champion data quality and governance, ensuring insights are consistent, trustworthy, and well-documented. • Build dashboards and analytics that provide key insights for executive leadership, GTM, product, and finance teams. • Analyze data to identify the best ways to deliver value to clients and inform product decisions.

Role Description We are seeking an experienced SAP Data Migration Engineer to design, execute, and support large-scale data migration initiatives within SAP S/4HANA environments. This role focuses on the full data migration lifecycle — extraction, transformation, validation, reconciliation, and cutover — to ensure accurate, complete, and compliant migration of enterprise data from legacy systems into SAP. The ideal candidate will combine strong hands-on experience with SAP LTMC, SLT, LVM, and S/4HANA migration tools with deep understanding of SAP data structures, business processes, and data governance, and will partner closely with functional teams, business owners, and infrastructure stakeholders during all phases of migration. Qualifications - Bachelor’s degree in Computer Science, Engineering, or a related technical discipline. - Five or more years of SAP data migration experience. - Strong hands-on experience with SAP LTMC and S/4HANA migration tools. - Experience with SAP SLT replication scenarios. - Working knowledge of SAP LVM for system refresh and landscape management. - Strong understanding of SAP master and transactional data structures. - Experience performing data validation and reconciliation processes. - Strong SQL and data analysis skills. - Experience working in enterprise SAP landscapes during major implementations. - Strong troubleshooting and documentation skills. Requirements - Design and execute SAP data migration strategies for S/4HANA implementations, including conversion and greenfield scenarios. - Perform data extraction from legacy systems using SAP-provided and custom tools and prepare data for ingestion into SAP. - Configure and utilize SAP LTMC (Legacy Transfer Migration Cockpit), including custom migration objects where required. - Implement real-time replication scenarios using SAP SLT (System Landscape Transformation), including transformation rules and filter conditions. - Manage logical system setups and replication configurations for hybrid SAP environments. - Support system refreshes and landscape virtualization activities using SAP LVM (Landscape Virtualization Management). - Design and execute data transformation, cleansing, and enrichment processes prior to migration. - Develop comprehensive validation and reconciliation reports to ensure data accuracy and completeness. - Identify and resolve data inconsistencies, duplicates, and orphan records prior to go-live. - Support mock migrations, dress rehearsals, and the final cutover, including detailed runbook execution and rollback planning. - Optimize performance for large-volume data loads, including parallelization, package sizing, and database tuning. - Collaborate with functional teams to validate master and transactional data against business expectations. - Ensure compliance with enterprise data governance, audit, and privacy standards. - Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures. Benefits - Competitive base salary commensurate with experience, plus benefits. - 100% remote, full-time, direct W2 position. - Long-term, multi-year engagement aligned to the Bright Vision SOW delivery roadmap.

Role Description 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. Qualifications - Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field required; advanced degree a plus. - 8–12+ years of experience in data engineering or data architecture, including 2+ years leading or managing engineers. - Advanced proficiency in SQL and data modeling, with strong architectural judgment. - Strong experience with ETL/ELT tools (e.g., Azure Data Factory, dbt, Informatica, Talend). - Hands-on experience with cloud data platforms (e.g., Snowflake, Azure, AWS). - Proven track record delivering large-scale data warehouses, data lakes, and BI solutions. - Familiarity with big data technologies (e.g., Spark, Hadoop ecosystem). - Experience working with healthcare data, including PHI/PII, preferred. - Demonstrated people leadership, project delivery, and stakeholder management skills. - Excellent communication, collaboration, and organizational skills. Requirements - 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. - 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. - 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. - 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. - 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. - 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. - Perform other related duties as assigned by leadership. Benefits - Supportive, progressive, fast-paced environment - Competitive pay structure - Matching 401(k) with immediate vesting - Medical, dental, vision, life, & short-term disability insurance