Data Engineer

• Own the product strategy and roadmap for Tanium’s cloud/SaaS data platform
• Define and drive the short- and long-term roadmap for Tanium’s end-to-end data architecture
• Partner with Product Managers, Engineering, Design, and leadership across the organization
• Lead product direction for how data is surfaced and experienced in Atlas and the UI
• Drive the strategy for data movement and integration capabilities
• Establish clear product requirements, technical specifications, use cases, business logic, and success metrics
• Partner with engineering leadership to make durable architectural decisions
• Champion data quality as a core product priority
• Collaborate with internal teams on enablement, training, and launch materials
• Work closely with business, technical, customer-facing, and go-to-market teams
• Leverage innovation and trends in cloud, SaaS, data architecture, analytics, and enterprise platform technologies to develop strategic solutions
• Build, lead, and develop a high-performing product team

Director, Product Management – Data Platform

• Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.
• Build and implement scalable solutions that align to our data governance standards and architectural roadmap for data integrations, data storage, reporting, and analytic solutions.
• Design, develop and test data integration solutions. Write, automate and document unit/integration/functional tests.
• Manage automated deployments using Git pipelines, ensuring code changes are efficiently version-controlled and deployed.
• Collaborate with multiple teams to streamline deployment workflows, monitor and troubleshoot pipelines for reliability and performance.
• Perform data analysis required to troubleshoot data-related issues by building a data quality framework and assist in the resolution of data issues.
• Serve as tech lead by mentoring less experienced members of the team through code reviews, pair programming and similar hands-on interactions.

Lead Data Engineer

• Design, build, and maintain scalable data pipelines across internal databases, vendor systems, and our data warehouse
• Support both batch and event-driven or CDC-based data workflows
• Improve pipeline reliability, observability, and performance
• Troubleshoot issues in production and proactively solve data quality or system problems
• Build and maintain data warehouse schemas and transformation layers to support analytics and operational use cases
• Communicate clearly about implementation choices, tradeoffs, and technical constraints
• Identify opportunities to improve data workflows through better tooling, automation, and engineering practices
• Help shape scalable patterns for how data is ingested, transformed, stored, and accessed

Senior Data Engineer

• Lead a team of data engineers and engineering managers building large-scale, real-time data pipelines in Spark
• Act as the primary technical liaison to business leadership, translating trade-offs between technology and business priorities in both directions
• Set the multi-year technical direction for Data Engineering and communicate that strategy across both technical and business audiences
• Partner with data scientists, analysts, and business stakeholders to turn business requirements into data products the team builds against
• Represent Data Engineering in cross-functional and executive planning, building alignment across engineering, product, and business leaders
• Set the architectural direction and standards for how data moves across platforms, from streaming ingestion through ETL to aggregation and analytics, hold your managers and teams accountable to that direction, and establish the engineering and agile practices that support delivery speed and quality
• Stay close to the technical details to guide architecture design decisions, performance tuning, and tradeoff calls, and to give your team the context they need to move quickly without waiting on you
• Work with your teams and the RV Data Platform team to design scalable solutions across distributed systems using AWS, Databricks, and modern big data technologies
• Champion a governance-first mindset across your team, making sure the way we collect, move, and use data protects the privacy of the people behind it
• Manage and develop the data engineering managers on your team, setting the bar for how they coach, hire, and run their teams
• Own career development across your org, building growth paths for individual contributors and managers alike, and coaching through regular, direct feedback
• Hold the team accountable for delivering high-quality, scalable solutions across the full data lifecycle

Director of Data Engineering

• You will own and evolve our data pipelines on GCP — building new ones, hardening existing ones, improving data quality, and making clean, trustworthy data available across the organisation.
• Designing ELT/ETL processes on BigQuery and ClickHouse, building real-time pipelines on Pub/Sub and Kafka with Dataflow (and where it fits, Flink/Spark).
• Orchestrating workflows with Airflow, and ensuring data is properly cleaned, modelled, and served for analytics, ML training, and online inference.
• Partnering with ML engineers on feature pipelines, monitoring data drift, and keeping models well-fed and retrained as needed.
• Consuming and building REST APIs, integrate with third-party SaaS sources, and treating infrastructure as code.
• Collaborating closely with Infrastructure, Software Engineering, Product, and ML/AI engineers.
• Helping drive the migration off Snowflake onto GCP-native stack — and retire shadow pipelines along the way.
• Owning the orchestration layer in Airflow, including SLAs, retries, and data quality gates.
• Modeling data for analytics and for ML — including feature pipelines that serve both training and low-latency online inference.
• Capturing requirements from stakeholders and translating them into pragmatic, well-scoped data products.
• Continuously improving data quality, reliability, observability, and cost efficiency.
• Identifying new data sources worth acquiring and integrating them cleanly.

• Leverage data and analytics to provide strategic insights
• Develop and implement innovative solutions to optimize business performance
• Build and maintain data pipelines and architectures
• Implement data visualization tools to provide actionable insights
• Collaborate with stakeholders to identify and address data challenges
• Coach and motivate teams to solve complex problems
• Validate outcomes with clients and act on feedback

Senior Data Engineer – Senior Manager

• Building and leading a team to deliver technology products and services that meet business outcomes.
• Developing a technology strategy, ensuring technology solutions comply with applicable standards.
• Promoting design, engineering, and organizational practices.
• Advocating and advancing modern, Agile solution delivery practices.
• Coaching, mentoring, providing feedback and hands-on career development.
• Identifying emerging talent and fostering leadership skills.
• Managing stakeholders and relationships with business and technology partners.
• Contributing to the technology strategy for their technical domain.
• Creating an inclusive and healthy working environment.

Senior Technical Manager – Enterprise Data Platform

• Build, maintain, and optimize ETL/ELT data pipelines for ingestion, transformation, and delivery of U.S. data assets
• Develop SQL, Python, and Spark based transformation logic for analytics and reporting needs
• Collaborate with the U.S. Data Architect to design data models and semantic structures aligned to business requirements
• Work with BI to deliver curated, validated datasets supporting dashboards, KPIs, and analytics
• Monitor pipeline performance, troubleshoot failures, and perform root cause analysis
• Implement data quality rules, validation routines, logging, and audit checks
• Support CRM data integration and ensure data consistency across source systems
• Document pipelines, schemas, transformation logic, and operational processes
• Participate in testing and deployment of data enhancements, integrations, and new data sources
• Coordinate with Governance teams to maintain lineage, metadata, and access controls
• Support cloud based engineering activities (Azure preferred)

• Lead a team of 2-3 engineers
• Working with fellow Nava engineers to design, review, and build well-crafted software
• Working in an agile manner to efficiently ship new features that meet user needs
• Design and develop scalable data ingestion and processing pipelines
• Implement large-scale data ecosystems within cloud-based platforms that include data management and data governance of structured and unstructured data
• Implement data validation and quality checks to ensure accuracy and consistency
• Work with cross-functional project teams to gather business requirements and translate to detailed technical specifications
• Work with Government partners to assist and develop data engineering applications and pipelines that will enable data services and processing capabilities
• Participate in software design and code reviews
• Maintain security and privacy standards in all aspects of the data pipeline
• Taking part in hiring activities (e.g., submitting referrals, conducting interviews, and attending interview debriefs), as needed

Senior Software Engineer, Data

• Design and implement the canonical data model for Vultr’s control plane ERP transformation: product catalog, chart of accounts, financial transactions, cost centers
• Build and maintain the internal APIs and event streams that Finance, Analytics, and downstream systems consume
• Refactor existing administer code toward clean domain boundaries (no more conflated orders/ledger/report tables)
• Implement data upgrade/migration paths from legacy schemas without breaking production
• Write the integration layer between administer and Vultr's existing billing, provisioning, and reporting systems
• Establish data validation and integrity checks across the financial data layer
• Collaborate with the Product Manager to translate finance domain requirements into durable schema designs
• Document architectural decisions and data model contracts for downstream consumers

Senior Software Engineer, ERP, Data & Domain

• Develop advanced data engineering solutions that power critical investment decisions
• Design robust data models and ETL pipelines
• Apply modern DevOps and Agile practices

• Lead the strategy and execution of complex and large Data and Analytics portfolio.
• Develop and implement a strategic roadmap to modernize legacy data and analytics ecosystems using Cloud and AI.
• Ensure data architecture and solutions align with enterprise-wide standards for Data, AI and Analytics.
• AI Data Engineering leader responsible for Implementing AI data pipelines that integrate structured, semi-structured, and unstructured data to support AI and Agentic solutions.
• Design, build and maintain scalable real-time data pipelines for efficient ingestion, processing, and delivery.
• Oversee the design, development, and maintenance of lakehouse architectures, data pipelines, data warehouses, data lakes and reporting systems.
• Mentor and lead a high-performing team including Directors, Business data analysts, Data engineers and Release train engineers.
• Identify and champion developer productivity improvements across the end-to-end data management lifecycle.

Director, Data Architect

• Lead moderately complex initiatives within Technology
• Build and maintain optimized and highly available data pipelines
• Review and analyze moderately complex business, operational or technical challenges
• Oversee data integration work, maintain a data warehouse and analytics environment
• Resolve moderately complex issues and lead teams to meet data engineering deliverables
• Collaborate and consult with colleagues and managers

• Perform applications database administration (Oracle and Snowflake) services including SQL code review, performance analysis, query tuning, database application design, physical data modeling, development support and Engineering.
• Proactively monitor databases servers and respond to any alerts
• Provide database support in all phases of SDLC and agile experience is preferred
• Participate in 24X7 on call rotation schedule for various production support, database maintenance, housekeeping and installs
• Work with enterprise teams for Systems Administrators, Cyber Security and Capacity Planning groups as and when situation demands
• Ability to quickly diagnose the problem areas and come up with solutions and/or workarounds
• Should have strong time management skills with willingness and ability to prioritize multiple projects/initiatives at the same time
• Establish database standards for operations, upgrades, migrations and onboarding new applications and/or clients
• Write clear, concise, well organized user documentation to maintain standards and procedures

Senior Data Engineer – Oracle RAC DBA

• Build and maintain the data models and transformations that power reporting in the Skimmer product, leveraging tools like Fivetran transformations, dbt, and Sigma Computing materializations
• Build and maintain customer-facing data models and reports in Sigma Computing, embedded within the Skimmer application
• Manage and extend ingestion using Fivetran across a growing set of sources
• Develop and maintain data transformations in Python and SQL against our Snowflake data warehouse
• Partner with product and engineering to turn customer needs into reliable, performant reporting experiences
• Collaborate with application engineers to understand source systems and ensure clean, reliable data capture
• Monitor data quality, reliability, and report performance, and troubleshoot issues as they arise
• Document data models, definitions, and architecture to support a growing team

• lead a team of data architects in the Asset Management Technology’s architecture team
• set the architectural direction for AI-ready platforms
• establish governance frameworks that enable consistent excellence
• build and develop high-performing data architecture teams
• architect and deliver high-impact solutions
• design and optimize enterprise-scale data platforms
• establish reference architectures and accelerators
• lead technical deep dives and design reviews

Vice President, Data Architecture

• Lead and develop the Data Architecture team, including data architects and modelers responsible for enterprise data design, modeling standards, and architectural direction
• Set the data architecture vision and roadmap for Circle K’s modern data platform, translating strategy into practical standards, reference architectures, and execution priorities
• Create focus and drive decisions across competing priorities, helping teams balance speed, quality, reuse, governance, and business value
• Guide source discovery and data assessment, including source system identification, data availability, freshness, latency, volume, velocity, and initial source-to-target mapping
• Define ingestion and raw layer architecture, including batch, streaming, CDC, API, and file-based patterns; raw/bronze landing schemas; and incremental load strategies
• Establish cleansed and standardized data structures, including silver layer schema design, data type standardization, format normalization, and consistent transformation patterns
• Own refined and dimensional modeling standards, including facts, dimensions, conformed dimensions, slowly changing dimensions, surrogate keys, business keys, grain definition, and referential relationships
• Design curated data products that integrate data across domains and are reusable, governed, versioned, and aligned to business consumption needs
• Influence semantic layer patterns that provide consistent business metrics, entities, hierarchies, and self-service analytics experiences
• Define reusable architecture patterns for ingestion, transformation, modeling, data products, semantic models, metadata, lineage, and quality controls
• Establish practical design review practices that improve quality and consistency without slowing delivery.

Senior Manager – Data Architecture

• Drive the Data Architecture and Data platform modernization for the Workplace Investing division
• Work with Enterprise Architects to modernize legacy systems
• Collaborate closely with business partners and technology teams

Director, AI/ML, Data Architecture

• Designs and develops moderately complex queries, objects, ETL packages, reporting structures, and other objects necessary to support detailed analysis and self-service reporting needs.
• Collaborates with analytics and business teams to create and improve data models that feed BI tools, increasing data accessibility, and fostering data-driven decision making across the organization.
• Takes ownership of the health, reliability, and security of the data platform by designing and implementing processes and solutions that proactively monitor data delivery across the full pipeline — ensuring data is accurate, complete, consistent, and timely from source ingestion through gold layer curation.
• Investigates, diagnoses, and resolves complex data pipeline failures across all system layers; uses findings to drive pipeline improvements and communicates status, root cause, and resolution clearly to the team throughout the full lifecycle of an incident.
• Assists with the development and delivery of data solutions, including data pipelines, API integration, and other structures and processes to support the data platform
• Identifies, designs, and implements internal process improvements, including the automation of manual processes, optimization of data delivery, and refactoring of code for improved performance
• Builds pipelines to enable the optimal extraction, transformation, and loading of data from a wide variety of data sources
• Provides strategic assistance to BI leadership and the BI team by making recommendations in the areas of data management and best practices
• Collaborates with developers, database administrators, data architects, and others on reporting and data management projects as needed
• Takes on other duties needed to help drive our Purpose, fulfill our Brand Principles, and abide by our Organization’s Values

Data Engineer II

• Leading and overseeing all data engineering functions
• Reporting directly to the Chief Data & Analytics Officer
• Owning the data delivery roadmap
• Ensuring the accuracy, consistency, and quality of all data solutions
• Providing strategic leadership in designing, building, and maintaining scalable data architectures, pipelines, and ETL workflows
• Leading and developing a high-performing team of Data Engineers
• Driving best practices in data engineering
• Ensuring successful delivery of complex data initiatives aligned with business objectives
• Collaborating effectively with Data Science, Business Intelligence and Technology teams to define success metrics and road map

Data Engineer jobs in North Carolina

See all jobs on JobTailor

Director, Product Management – Data Platform

Lead Data Engineer

Senior Data Engineer

Director of Data Engineering

Senior Data Engineer

Senior Data Engineer – Senior Manager

Senior Technical Manager – Enterprise Data Platform

Data Engineer

Senior Software Engineer, Data

Senior Software Engineer, ERP, Data & Domain

Senior Data Engineer

Director, Data Architect

Senior Data Engineer

Senior Data Engineer – Oracle RAC DBA

Data Engineer

Vice President, Data Architecture

Senior Manager – Data Architecture

Director, AI/ML, Data Architecture

Data Engineer II

Director of Data Engineering