Data Engineer

• Serves as a lead in the analysis of business requirements associated with the design and implementation of highly complex, highly scalable enterprise data processes
• Designs and develops robust and efficient processes for extracting, loading and transforming data to meet the needs of enterprise scale projects
• Provides guidance and participates in activities involved in the analysis, design, development, troubleshooting, debugging and maintenance of an enterprise data management and data ecosystem
• Identifies, investigates, tracks, and resolves the most complex technical errors ensuring the solution is timely and of acceptable quality
• Establishes and enforces database standards, guidelines, procedures and quality assurance for database deliverables such as conceptual design, logical data model capacity planning, external data interface specs, data loading, data maintenance plan and security
• Reviews and analyzes data objects and models to improve data management and data access
• Designs, constructs, tests and implements extraction and transformation programs, processes and cycles for historical and current source data
• Creates technical specification for supporting enterprise data transformation processes and supplementing system documentation for ETL processes
• Performs data profiling, source-target mappings, data transformation development, optimization, testing and implementation
• This position participates and serves as a lead in maintaining the ETL environment for the company’s system-wide enterprise data warehouse.

Supply Chain Data Engineer

• Design and develop data serving and semantic layers to support business needs
• Develop data models for use by analysts and applications using modern dimensional modeling practices
• Build and maintain robust, scalable data pipelines using ETL, ELT processes
• Create efficient and performant data models to support business requirements
• Implement and automate data quality checks and monitoring to ensure data accuracy
• Manage, troubleshoot and optimize existing data infrastructure, including cloud-based solutions
• Leverage cloud data platforms (Fabric, Databricks, Snowflake, etc.) for data storage, processing, and analysis
• Collaborate with data analysts, data scientists, and business stakeholders to understand their data needs

• Design, build, and optimize robust ETL/ELT processing pipelines to ingest and transform complex healthcare data from disparate sources
• Architect and maintain scalable data solutions utilizing Snowflake as our primary data cloud, leveraging both Azure and AWS environments
• Build and maintain a robust semantic layer to translate complex data structures into business-friendly metrics
• Collaborate closely with data leadership to synchronize disparate data streams, ensuring data quality and the successful deployment of Customer 360 initiatives
• Ensure all data architecture, storage, and processing strictly adhere to healthcare compliance standards (e.g., HIPAA, HITRUST) and best practices for handling Protected Health Information (PHI)

Senior Data Engineer

• Apply knowledge of health care and database management to analyze clinical data, and to identify and report trends.
• Design and build modern data-centric software applications to support clinical and operational processes across all parts of the healthcare system.
• Work closely with the Product, Platform, and Architecture teams to deliver on joint efforts.
• Build data pipelines and transformations, data enrichment processes, provisioning layers, and user interfaces to meet the requirements of key initiatives.
• Mentor and assist less experienced Data Engineers and participate in research and development of new technologies to help set up repeatable processes or templates for other Data Engineers to follow.

Senior Data Engineer IS

• Deploy new data pipelines
• Design & build data observability platforms and metrics
• Build metadata driven pipeline solutions
• Monitor and optimize data transformations
• Build third party data integrations

• Own End-to-End Delivery of Core Data Platform Components
• Design and ship the data normalization, schema mapping, validation, enrichment, and distribution pipeline for a net-new intelligent data warehouse
• Write production code as a hands-on individual contributor. This is not a role that delegates implementation to others
• Take technical ownership from architecture through deployment, with accountability for reliability, performance, and correctness
• Drive Technical Architecture
• Partner with a small seed team of senior engineers to define the end-to-end architecture for an AI-native data warehouse serving institutional financial clients
• Bring opinionated decisions on schema design, normalization strategies, API exposure patterns, and data distribution approaches
• Evaluate and select technologies with a bias toward what ships well and scales sustainably
• Build AI Evaluation Infrastructure
• Design and implement the evaluation framework that makes AI-generated outputs trustworthy in high-stakes financial data contexts
• Build cross-model comparison tooling, deterministic validation checks, and human-in-the-loop review workflows
• Contribute to shared AI infrastructure that will serve as a foundation for multiple products across the company
• Ship with AI-Native Development Practices
• Use agentic coding tools and LLM-assisted development as your primary workflow; this is how the entire team operates
• Bring strong opinions about how to get the most out of AI-assisted development while maintaining quality and reliability
• Contribute to the team’s evolving practices around AI-accelerated SDLC
• Establish Technical Standards
• As an early senior voice on a new team, set coding standards, review practices, and architectural documentation that will scale
• Help define what “good” looks like for a team building at speed without sacrificing quality
• Mentor and provide technical guidance as the team grows from seed squad to full delivery organization
• Collaborate Across Engineering and Product
• Work closely with your engineering manager, peer engineers, and product management to translate requirements into executable technical plans
• Participate actively in design reviews and roadmap discussions with grounded, implementation-level perspective
• Engage directly with the nuances of private markets data – fund administration, investment data schemas, institutional reporting workflows – to build domain intuition that improves your technical decisions

Staff Software Engineer, Data Platform

• Apply knowledge of health care and database management to analyze clinical data, and to identify and report trends.
• Design and build modern data-centric software applications to support clinical and operational processes across all parts of the healthcare system.
• Build data pipelines and transformations, data enrichment processes, provisioning layers, and user interfaces to meet the requirements of key initiatives.
• Mentor and assist less experienced Data Engineers.
• Participate in research and development of new technologies to help set up repeatable processes or templates for other Data Engineers to follow.
• Collaborate with Product, Platform, and Architecture teams to deliver on joint efforts.

• Management of Cogito suite of reporting tools
• Cogito Security management
• Maintenance of Cogito Related System Wide Settings
• Coordinates Analytics Processes/build across all Epic Applications
• Oversite of Cogito Tools build and provisioning standards
• Coordinating, auditing, troubleshooting technical system functionality – including reporting queues
• Represent Cogito in Epic governance groups
• Coordination & Management of Cogito related projects – including Epic Releases

Data Engineer II

• Define and evolve CFC-wide data architecture across all major systems and platforms
• Establish clear data domains, system boundaries, and integration patterns
• Assess current and future organizational data needs and translate them into architectural direction
• Develop long-term data architecture patterns that balance scalability, maintainability, and delivery constraints
• Design and maintain conceptual, logical, and physical data models representing CFC’s core entities, relationships, and measures
• Define, document, and govern source system schemas including canonical fields, data types, naming standards, and versioning approaches
• Establish systems of record and systems of reference for key domains such as accounts, licenses, users, and programs
• Ensure consistent implementation of data models across operational systems
• Create clear documentation that enables shared understanding across technical and non-technical stakeholders
• Architect and guide data flows between CFC systems to support operations, analytics, research, and decision-making
• Design integration and transformation approaches that preserve semantic meaning
• Oversee large-scale data integration, transformation, and storage patterns for reliable analytics
• Monitor and evolve data flows to reduce duplication, fragility, and unnecessary complexity
• Embed privacy, security, and compliance requirements directly into data models and integrations
• Partner with IT, security, and legal teams to align architecture with regulatory and policy requirements
• Ensure privacy and security protocols, including field-level encryption, role-based access control, deletion, and auditing are architected into and consistently supported across CFC’s data architecture
• Define data quality standards and validation strategies, including management of schema drift over time
• Enablement & Collaboration
• Work closely with engineers, analysts, researchers, data stewards, and business partners
• Serve as a subject-matter expert on CFC’s data architecture
• Communicate complex data concepts clearly to diverse audiences

Principal Data Architect

• Design the vision and blueprint of an organization’s data framework.
• Design and manage data systems, set policies for how data is stored and accessed, coordinate various data sources within an organization, and integrate new data technologies into existing IT infrastructures.
• Data modeling and design, including software development and database administration.

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Supply Chain Data Engineer

Data Engineer

Senior Data Engineer

Senior Data Engineer IS

Data Engineer

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Senior Data Engineer

Data Engineer II

Principal Data Architect

Data Architect – Data Ecosystems