Data Engineer

• Build and operate the financial data plane for Numeric’s Financial Data Platform
• Develop scalable ingestion from APIs including NetSuite, Stripe, Brex, Ramp, and HubSpot
• Build file-based S3 inboxes and Postgres-to-ClickHouse replication
• Enforce data contracts and typed source data at system boundaries
• Manage lakehouse schemas through declare, codegen, and apply pipelines
• Scope queries, build ACLs, and protect customer data
• Develop batch processing and event-driven accounting systems
• Improve data correctness, observability, ingestion health, re-ingestion, and traceability from ledger entries to raw events
• Design reporting query patterns and materializations for scalable drill-downs
• Own a slice of the architecture end to end
• Collaborate with accounting module engineers, reporting teams, and AI agents
• Learn the accounting domain and help shape product direction

Software Engineer, Data Platform

• Collaborate across Agile teams to design, develop, test, implement, and support technical solutions
• Influence teams of developers, data analysts, and data scientists across machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Use Python and Spark, open-source relational and NoSQL databases, Databricks, Snowflake, and cloud-based data warehousing platforms
• Stay current with data trends, experiment with new technologies, participate in technology communities, and mentor data community members
• Collaborate with product managers and software engineers to deliver cloud-first data solutions supporting millions of Americans
• Independently design, build, and deliver cloud data solutions and applications
• Architect and enforce data engineering design patterns for code quality, maintainability, and reusability
• Communicate technical concepts and data outcomes to internal and external stakeholders
• Design and build scalable, resilient, and operationally efficient data pipelines and platforms
• Implement data security standards, including encryption and fine-grained access control, while ensuring privacy compliance

• Define and implement enterprise data architecture strategy aligned with business objectives
• Design scalable, secure, and high-performing data platforms for analytics, reporting, AI/ML, and operational workloads
• Develop conceptual, logical, and physical data models for enterprise applications
• Architect enterprise data warehouses, data lakes, lakehouses, and modern data platforms
• Establish data governance, metadata management, data quality, and master data management frameworks
• Lead data integration and ETL/ELT architecture across multiple systems
• Define data management standards, best practices, and architectural guidelines
• Collaborate with business leaders, enterprise architects, and technology teams on data transformation initiatives
• Evaluate emerging technologies and recommend data solutions
• Provide technical leadership and mentorship to data engineering and analytics teams
• Ensure compliance with security, privacy, and regulatory requirements
• Lead enterprise data architecture discussions and governance forums
• Drive architecture reviews and design approvals
• Support pre-sales activities, solution proposals, and technical estimations
• Engage executive stakeholders to define long-term data strategies
• Establish reusable architecture standards and frameworks across projects

Assistant Vice President – Data Architect

• Build, maintain, and optimize data pipelines for ingestion, transformation, and delivery
• Develop and maintain data models supporting reporting and analytics use cases
• Contribute to reliable, reusable data products
• Support onboarding of new data sources
• Write efficient, scalable SQL queries and contribute to performance optimization
• Monitor and troubleshoot data pipelines for reliability, performance, and accuracy
• Implement and support data quality checks and validation processes
• Apply established data governance standards within data engineering workflows
• Document data architecture, pipelines, and workflows
• Work cross-functionally with business and technology teams to deliver timely, high-quality data
• Contribute to DataOps processes and data engineering standards and best practices
• Assist in evaluating new tools and technologies

Associate Data Engineer

• Design, build, and optimize data pipelines for ingestion, transformation, and delivery
• Develop and maintain scalable data architectures, including data lakes and data warehouses
• Build reliable, reusable data products and data models supporting reporting, analytics, AI, machine learning, and business operations
• Optimize performance across data platforms and pipelines
• Ensure data is clean, reliable, accessible, and available for enterprise use
• Apply data governance, quality, lineage, and security standards within data engineering solutions
• Support delivery of trusted and consistent enterprise data
• Partner cross-functionally with business and technology teams to deliver timely, high-quality data
• Help define and implement DataOps and data engineering best practices
• Mentor junior data engineers and promote data engineering best practices

Senior Data Engineer

• Contribute to the design and implementation of scalable data infrastructure, pipelines, and models for core data assets
• Drive code quality, reliability, and engineering best practices across the data stack
• Partner with the Risk team to build robust, automated data pipelines for insurance reporting processes, including actuarial and bordereaux reports
• Design and implement data integration solutions to consolidate siloed datasets across the organization
• Establish unified data models and improve data accessibility
• Build and maintain data infrastructure enabling self-service analytics
• Enforce data governance, quality controls, and security standards

• Design and optimize pipelines that ingest, transform, and distribute large-scale document data
• Build and maintain reliable, high-performance backend services for document storage, retrieval, and processing
• Implement data governance, privacy controls, audit trails, and regulatory compliance requirements, including GDPR
• Lead database migrations and improve schema design, query performance, and data scalability
• Partner with machine learning and AI teams to support model training and inference at scale
• Mentor engineers on platform architecture, engineering practices, and system design

Senior Data Platform Engineer

• Lead data strategy for product capabilities and competitiveness
• Identify, integrate, sort, and place data infrastructure for parts ordering, customer need-by dates, and logistics cycle times
• Collaborate cross-functionally with information technology, sourcing, engineering, and other teams
• Set strategy and improve measurement methods and accuracy for safety, quality, on-time delivery, and cost
• Execute large-scale data analytics to solve operational challenges such as logistics network optimization and consolidation
• Develop strategic operational improvements including safety-stock adjustments and lead-time reductions
• Devise and use algorithms and models to mine big data stores and perform data and error analysis
• Improve predictive models for digital maintenance, repair and outages, and non-capital parts demand forecasting
• Analyze historical and incoming data for trends and patterns
• Interpret data and provide actionable output signals to relevant functions
• Identify cost-reduction opportunities while maintaining or improving quality and on-time delivery
• Clearly communicate analytic solutions to stakeholders
• Project manage and collaborate cross-functionally to implement process improvements through project realization
• Drive configurability across plant/product modules to optimize total solution value and meet market/customer needs
• Influence and collaborate with horizontal functional partners on effective decisions

Lead Systems/Data Architect – Power Product Management Strategist

• Own the technical roadmap for the data platform
• Balance scalability, reliability, security, compliance, and business priorities
• Architect next-generation pipelines and storage systems for high-volume document data
• Lead technology selection, system design, and infrastructure strategy decisions
• Advance data governance, privacy controls, compliance frameworks, and audit capabilities
• Partner with machine learning and AI leaders on model training, evaluation, and inference at scale
• Establish technical standards and mentor engineers
• Help build a high-performing platform organization
• Represent the platform function in company-wide architecture and engineering decisions
• Own critical systems and contribute code to solve complex technical challenges

Staff Data Platform Engineer

• Build reliable, monitored CDC pipelines from production databases (MariaDB, PostgreSQL, MongoDB) into the S3 + Iceberg lake and Snowflake
• Stand up a transformation layer such as dbt on Snowflake so core business metrics come from tested, version-controlled models
• Select and implement an orchestration tool so pipelines and dashboard refreshes run automatically, with alerting when they break
• Design and enforce access controls for patient data, including row/column-level PHI restrictions, HIPAA Safe Harbor compliance, anonymization pipelines, and account deletion workflows
• Establish a single governed copy of production data for analytics, finance, and AI teams
• Support the AI team's data needs for model training
• Design and build warehouse architecture with raw, transformed, and business-ready layers powering executive dashboards
• Serve as Doctronic's first dedicated data engineer and own data plumbing end to end
• Work with AI engineering, product, finance, partnerships, data, marketing, and other stakeholders