Role Description Everforth ECS is seeking a Data Engineer to work on our US Postal Service Data Analytics team. This is an exciting position that develops, implements, and maintains data workflow and architecture solutions across large enterprise warehouses and pipelines. These solutions will be used to support effective and efficient data management and enterprise-wide business intelligence and efficiency analytics for the US Postal Service. - Implement and optimize data pipeline architectures for data sourcing, ingestion, transformation, and extraction processes, ensuring data integrity, consistency, and compliance with organizational standards. - Develop and maintain scalable database schemas, data models, and data warehouse structures; perform data mapping, schema evolution, and integration between source systems, staging areas, and data marts. - Automate data extraction workflows and develop comprehensive technical documentation for ETL/ELT procedures; collaborate with cross-functional teams to translate business requirements into technical specifications and data schemas. - Establish and enforce data governance standards, including data quality metrics, validation rules, and best practices for data warehouse design, architecture, and tooling. - Develop, test, and deploy ETL/ELT scripts and programs using SQL, Python, Spark, or other relevant languages; optimize code for performance, scalability, and resource utilization. - Implement and tune data warehouse systems, focusing on query performance, batch processing efficiency, and resource management; utilize indexing, partitioning, and caching strategies. - Perform advanced data analysis, validation, and profiling using SQL and scripting languages; develop data models, dashboards, and reports in collaboration with stakeholders. - Conduct testing and validation of ETL workflows to ensure data loads meet scheduled SLAs and business quality standards; document testing protocols, results, and remediation steps. - Perform root cause analysis for data processing failures, troubleshoot production issues, and implement corrective actions; validate data accuracy and consistency across systems; support iterative development and continuous improvement of data pipelines. Qualifications - Must be a US Citizen or Green Card holder, and must be able to obtain a Public Trust Clearance. - 5-10+ years of experience building and designing data extraction, formatting and engineering tools, workflows, pipelines and ETL / ELT processes. - Detail oriented with strong analytical and problem-solving skills. - Ability to use database tools, techniques, and applications (e.g., Teradata, Oracle, Non-Relational) to develop complex SQL statements (e.g., multi-join), and to tune and troubleshoot queries for optimal performance. - Skill using Unix/Linux shell scripting to develop and implement automation scripts for Extract, Transfer Load (ETL) processes. - Communications skills (both verbal & written) - ability to work and communicate with all levels in team structure. - Team player with the ability to prioritize and multi-task, work in a fast-paced environment, and effectively manage time. - Java/J2EE and REST APIs, Web Services and building event-driven Micro Services and Kafka streaming using Schema registry, OAuth authentication. - Spring Framework and GCP Services in public cloud infrastructure, Git, CI/CD pipeline and containerization, data ingestion/data modeling. - Develop Microservices using Java/J2EE Spring for ingesting large volume real-time events into Kafka topics. Architect solutions that make the data available to consumers in real time. Requirements - Salary Range: $130,000-$145,000 Benefits - General Description of Benefits

• Design and implement scalable data models and pipelines on Snowflake using Snowpark and SQL • Write complex, production-grade SQL (dbt models, views, UDFs) to power business logic and product features • Build data-facing application layers using Streamlit (in Snowflake) or similar frameworks • Develop and iterate on greenfield product features across AI Pod and Rights360 platforms • Create user-facing applications on Snowflake, with potential extension into lightweight APIs (e.g. FastAPI) • Leverage Snowflake Cortex AI/ML services for forecasting, profitability modelling, and conversational/agentic features • Contribute to real-time inventory management and rights conflict detection (Rights360) • Build conversational interfaces enabling natural language data querying for operational teams • Collaborate closely with the shared tech lead across multiple workstreams • Take end-to-end ownership of solutions — from data modelling and logic to UI delivery • Ensure production-ready systems with a focus on reliability, maintainability, and clean code • Work across the full stack, from data pipelines to user-facing dashboards

Role Description Assist direct manager in overseeing and leading clinical data abstractors and related operations. Partner with the Lead Quality Abstractor, and the team’s software engineers and data management specialists to operationalize end-to-end abstraction, clinical data management workflows and activities, and lending technical support. Serve as the first line of communication and point of escalation amongst the data abstractors. - Front-line Staff Support: Serve as the primary liaison and initial point of escalation for all abstraction/team-related issues, questions, and concerns. - New Hire Onboarding and Training: Lead training new abstractors and provide ongoing guidance until released into production level activities by supporting the development and implementation of training workflows. - Mentoring and Subject Matter Expertise (SME): Provide ongoing clinical guidance and mentorship to existing abstraction team members, fostering professional development. - Technical Support: - Lead ongoing clinical and medical guidance to engineering, data management specialists, and technical staff to ensure the development of bug-free data for systems such as Electronic Data Capture Systems (ECDs), applications, and workflows. - Apply Medical Coding and Classification skills to support the creation of data standardization and harmonization rules. - Apply Data Management knowledge (e.g., CGDM, GCP) to support establishing logical relationships between clinical events within database schemas. - Apply Technical Skills to translate abstraction and encoding requirements to technical product requirements. - Data Abstraction: Advanced level review, interpretation, abstraction and data encoding. Less than 5% of patients require quality review. - Quality Assurance and Control: Apply and lead efforts in resolving complex or ambiguous data abstraction questions. - Protocol Adherence: Support developing and ensuring strict adherence to all project and research protocols. - Reporting: Track, analyze, and report on key abstraction and staff level metrics. - Process Improvement: Collaborate with cross-functional teams to effectively operationalize new abstraction activities. - Daily Operations: Support direct manager in daily coordination of the clinical data abstraction team's activities and workload distribution. - Conferences and Certifications: Maintenance of all relevant clinical or technical licensures. Attend conferences relevant to role and clinical field. - Other duties and responsibilities to be performed as assigned. Qualifications - Clinical Background: U.S. licensed Nurse, PA-C, NP, or DNP is required with a Master’s degree in health sciences. - Clinical Experience: Minimum of 5-6 years of experience in clinical data abstraction and medical records review, preferably in cancer, women’s health, rare diseases. - Lead Experience: Minimum of 2-3 years of direct experience supervising staff or providing team lead support to senior level management. - Quality and Compliance: Demonstrated commitment to data integrity, quality control processes, and adherence to HIPAA and other data privacy regulations. - Technical Proficiency: Proficient with Microsoft Office Suite or Google Suite, creating pivot tables, creating reports, data analysis, and using systems or databases common in data abstraction, research, or clinical data management. - Certifications/Industry Expertise: CCDM, CCRP, ACR-P, or CRA preferred. - Communication: Excellent written and verbal communication skills, with the ability to effectively collaborate with clinical and non-clinical teams. - Autonomy: Proven ability to work independently, manage time effectively, prioritize and organize tasks, and meet strict productivity and quality deadlines. - General Expertise: - Possess a high level of initiative and self-motivation. - Team player; can navigate supporting highly visible projects and tasks. - In-depth attention to detail and a fast learner. - Responding to shifting priorities and changes. Requirements - Compensation Range: $145,800 — $182,200 USD Benefits - Annual performance incentive bonus - Long-term equity awards - Comprehensive health benefits (medical, dental, vision) - 401(k) with company match - Generous paid time off and company holidays - Additional wellness and work-life benefits

• Design, develop, and execute end-to-end SAP data migration solutions for Finance (FI) and Supply Chain Management (SCM) data objects within a classified Red Network environment, operating under strict data handling, transfer, and validation protocols • Lead data migration workstream activities including legacy data analysis, data mapping, transformation rule development, migration object build, mock migration execution, reconciliation, and cutover planning • Develop and maintain data migration programs using SAP-native migration toolsets including SAP Data Migration Cockpit (LTMC/LTMOM), SAP LSMW (Legacy System Migration Workbench), and custom ABAP migration programs (BDC, BAPI, direct input methods) • Perform detailed analysis of legacy FI and SCM source data including general ledger balances, open items (AR/AP), asset master and values, material master records, inventory balances, open purchase orders, and open sales orders to define extraction, cleansing, and transformation requirements • Design and implement data cleansing, deduplication, and transformation logic to ensure source data meets SAP target structure requirements and federal data quality standards prior to load execution • Define and execute data validation frameworks including pre-load validation rules, post-load reconciliation checks, balance verification, and exception reporting to ensure migration completeness and accuracy • Coordinate data transfer activities across the Red Network boundary in strict compliance with classified data handling procedures, cross-domain solution (CDS) protocols, and agency-approved data movement authorization processes • Collaborate with FI and SCM functional consultants, enterprise architects, and federal IT security personnel to align migration designs with system configuration, authorization concepts, and classified environment constraints • Develop and maintain data migration documentation including migration strategy documents, object specifications, mapping workbooks, test results, reconciliation reports, and cutover runbooks • Support mock migration cycles, dress rehearsal runs, and production cutover execution, providing real-time reconciliation analysis and issue resolution within the constraints of the classified operating environment