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

• 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

• Develops, documents, tests, debugs, and maintains data; provides expertise and familiarity in software tools, frameworks and best practices in secure software engineering.
• Collaborates effectively with other members of the team to deliver on the team’s backlog.
• Participates in the discussion and implementation around complex capabilities.
• Develops complex features and capabilities to enhance the Early Warning core product offerings.
• Manages source code using Git.
• Receives, reviews and approves pull requests ensuring that code quality remains high.
• Processes both real time stream data and file based data through ETL frameworks and persist the data into the data store.
• Builds aggregations on the data to enable provisioning of data to the AI/ML models as input and also deliver them to the customers.
• Document complex details and decisions in Confluence.
• Builds automated tests alongside sprint work that is integrated into the CI/CD pipeline, considering environment variables, and provides recommendations.
• Able to troubleshoot complex bugs that may arise during development.
• Support the company’s commitment to risk management and protecting the integrity and confidentiality of systems and data.

Senior Software Engineer – Data Engineering

• 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

• Design, develop and maintain scalable and efficient data pipelines and ETL processes
• Collaborate with analysts and stakeholders to gather requirements and implement data solutions that meet business needs
• Proposes & designs data solutions to address complex business needs
• Prepare technical and procedural documentation required
• Participate in code reviews & testing
• Develop and manage data integrations between various systems, ensuring seamless data flow and consistency
• Optimize database and query performance to support analytical workloads
• Monitor and troubleshoot data workflows to ensure data quality and integrity

• design, build, and support secure, scalable cloud data solutions
• develop ETL pipelines, reusable PySpark patterns, and integrated data flows
• ensure compliance with IT policies, procedures, and industry standards
• design transaction specific application performance monitoring metrics
• implement Azure DevOps CI/CD practices and apply test-driven development where appropriate
• collaborate with stakeholders and provide technical guidance
• lead the strategic planning of a project as it relates to technical solution design
• design and implement engineering principles aimed at reliability practices and sound recovery procedures
• develop and maintain technical documentation, including system configurations and procedures

Staff Engineer II – Data Engineer

• 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

• Develop, implement, and maintain enterprise data management solutions
• Assist with the development, implementation, and maintenance of an overall organizational data strategy
• Design and build data processing flows to extract data from various sources
• Load data into data storage systems
• Transform data using industry-standard techniques

• 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

• Serve as a hands-on technical leader responsible for designing, building, and optimizing Cambridge's modern data platform.
• Help define data architecture standards, lead engineering efforts, mentor team members, and drive scalable data solutions.
• Design, develop, and maintain scalable data pipelines supporting enterprise reporting, analytics, and business applications.
• Build and optimize ETL/ELT solutions using modern cloud-based technologies.
• Design and implement data integration solutions utilizing Azure Data Factory (ADF), Azure Functions, and other Azure services.
• Develop and maintain datasets within Snowflake and Azure Data Lake Storage (ADLS) environments.
• Lead data platform architecture initiatives, including data modeling, ingestion, transformation, storage, and consumption patterns.
• Drive performance tuning and cost optimization efforts across cloud data platforms and processing workloads.
• Design secure, reliable data movement solutions using batch and streaming integration patterns.
• Establish engineering best practices, code reviews, and architectural standards.
• Mentor data engineers and provide technical leadership across projects.
• Partner with analytics, product, and business stakeholders to deliver scalable, high-quality data solutions.

Principal Data Engineer

• Design, develop, and run tooling to discover problems in data and applications and report the issues to engineering and product leadership
• Review and analyze complex software enhancement initiatives for business, operational or technical improvements that require in depth evaluation of multiple factors including intangibles or unprecedented factors
• Make decisions in complex and multi-faceted data engineering situations requiring understanding of software package options and programming language and compliance requirements that influence and lead Technology to meet deliverables and drive organizational change
• Create standardized feature transformation pipelines and a common feature store with strong lineage, dictionary and high availability for models
• Implement robust data modeling (dimensional, data vault, or canonical models)
• Enforce data quality, lineage, and observability using standardized metrics, validation rules, and monitoring dashboards.
• Document patterns, runbooks, and best practices, and provide enablement through workshops and code examples

Lead Data Engineer

• Solving our unique data-lake challenges: transforming and seamlessly normalizing highly varied partner datasets (such as donation data);
• Design robust batch-processing pipelines capable of extracting and loading massive datasets from a variety of internal, external, and public sources;
• Developing processes for data mining, data modeling, and data production;
• Leveraging modern technology knowledge to champion evolving industry trends, updated design patterns, and engineering excellence across the team;
• Autonomously scope, design, and execute complex data projects from day one, turning ambiguous requirements into clear, decisive technical plans;
• Developing robust testing and monitoring systems for scheduled processes;
• Collaborating with cross-functional teams to support their data infrastructure needs;
• Joining each and every one of your colleagues in creating an inclusive workspace.

Staff Data Engineer

• Collaborate with key data and technology stakeholders to build out the enterprise data architecture practice
• Establish data architecture models and standards
• Guide teams to build out semantic and object standards for data taxonomies, models, flows, and diagrams
• Produce and maintain enterprise data architecture artifacts and support governance
• Create data reference architectures and document data flows
• Lead development of data modeling standards, best practices, and guidelines
• Oversee metadata, master data, and reference data management
• Measure progress against objectives with follow-up

Senior Enterprise Architect, Enterprise Data Architect

• drive the strategy and delivery of scalable, high-impact technology solutions supporting healthcare providers
• partner across product and engineering to deliver enterprise provider data transformation, modernization and engineering excellence across mission-critical platforms

Lead Director – Provider Data Engineering, Transformation

• Collaborate with other Engineers and Architects to define the enterprise data architecture roadmap.
• Drive the design and optimization of OLTP and OLAP models for scalability, performance, and maintainability.
• Establish standards for data modeling, storage, and integration across systems.
• Partner with other key stakeholders within engineering in developing a comprehensive data and BI strategy aligned with business objectives.
• Define data governance practices, data access control, compliance, and quality standards.
• Lead proof-of-concepts (POCs) for new data technologies and frameworks.
• Own the architectural review process and guidance to development teams on data-related projects.
• Establish and ensure best patterns and practices for ORM usage (Entity Framework and others) and SQL optimization, according to business needs.
• Evaluate and recommend where AI/ML can enhance data-driven decision-making.
• Stay current with modern data engineering trends, cloud-native architectures, and big data platforms.
• Actively participate and take ownership of Data Architecture artifacts via ADR process.
• Drive AI adoption by introducing and guiding teams in leveraging AI capabilities within the data engineering space to enhance internal efficiency, innovation, and decision-making in everyday workflows.
• Liaison between technology and product teams assisting teams in translating business requirements into tangible architectures that meet business needs now in and in the future.
• Design data architectures that accurately reflect and support evolving complex product and business processes and are required by our customer base.
• Lead data architecture initiatives, collaborating with cross functional teams, from concept through implementation, including governance and quality frameworks.
• Identify opportunities for predictive analytics and advanced modeling.
• Support and promote the company values through positive interactions with both internal and external stakeholders on a regular basis.
• Other strategic business initiatives or special cross-functional project involvement as required.

Data Architect

• Leveraging data and analytics to provide strategic insights and drive informed decision-making for clients
• Developing and implementing innovative solutions to optimize business performance and enhance competitive advantage (solution optimization and roadmap development)
• Utilizing advanced analytics techniques to support client operations and strategic goals (AWS data engineering and Redshift)
• Building and maintaining data pipelines and architectures to support business intelligence efforts (DataStage, ETL)
• Implementing data visualization tools to provide actionable insights and improve client outcomes (SQL Server, DB2)
• Collaborating with stakeholders to identify and address data challenges and opportunities (Managed services, and SLAs)
• Coaching and motivating teams to solve complex problems and deliver quality results
• Applying systems thinking to identify underlying problems and opportunities within client projects (workload orchestration and scheduling)
• Validating outcomes with clients and acting on feedback to refine solutions (CSAT and performance tuning)
• Directing teams through ambiguous and challenging situations with composure and sound judgment

• Developing and implementing data-driven solutions to optimize business performance and enhance competitive advantage (data engineering, ETL)
• Leveraging advanced analytics techniques to provide strategic insights and drive informed decision-making for clients (SQL optimization)
• Building and maintaining data pipelines to support efficient data collection and analysis (DataStage)
• Utilizing business intelligence tools such as Oracle Business Intelligence and QlikView to create comprehensive reports and dashboards (DB2, SQL Server)
• Collaborating with team members to gather and analyze data from various sources to discern patterns and trends (star schemas, dimensions)
• Applying data architecture development skills to design and maintain robust database management systems (snowflake models)
• Engaging in continuous process improvement to enhance data quality and integrity
• Supporting client engagement by actively listening and responding to diverse perspectives and needs (regulated environments)
• Participating in the development of business cases and market development strategies through data analysis and interpretation
• Adapting to a fast-paced environment and taking ownership of tasks to consistently deliver quality work (job scheduling, UNIX)

Data Engineer – Experienced Associate

• Developing and implementing innovative data solutions to optimize business performance and enhance competitive advantage
• Leveraging advanced analytics techniques to drive insights and support informed business decisions for clients (DB2, SQL Server)
• Building and maintaining data pipelines and architectures to support data collection and analysis (DataStage, ETL)
• Utilizing business intelligence tools such as Oracle Business Intelligence and QlikView to create insightful reports and dashboards (AWS, Redshift)
• Collaborating with stakeholders to identify data challenges and opportunities for continuous process improvement (GoldenGate, CDC)
• Applying analytical thinking and data science skills to interpret complex data sets and inform strategic recommendations
• Engaging in stakeholder management to foster meaningful client connections and anticipate their needs (managed services)
• Navigating complex situations to deliver quality work and contribute to personal and professional growth (Workload Scheduler)

Senior Associate – Data Engineer

• Leading data engineering projects to drive strategic insights and optimize business performance (ETL/ELT integration)
• Developing and implementing innovative data solutions using advanced analytics techniques (DataStage)
• Managing and mentoring teams to enhance their skills and deliver quality client services (pipeline architecture)
• Utilizing business intelligence tools and cloud-based analytics platforms to improve data-driven decision-making (AWS & Redshift)
• Building and maintaining data pipelines and architectures to support analytics initiatives (DB2, SQL Server)
• Collaborating with stakeholders to identify opportunities for data utilization and process improvement (GoldenGate & CDC)
• Overseeing the deployment of scalable data visualization and reporting solutions (performance tuning)
• Promoting the adoption of new technologies and methodologies within data and analytics teams (S3, Glue)

Data Engineer jobs in Arizona

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Senior Data Engineer

Senior Data Engineer – Senior Manager

Senior Software Engineer – Data Engineering

Senior Software Engineer, Data

Senior Software Engineer, ERP, Data & Domain

Senior Data Engineer

Staff Engineer II – Data Engineer

Senior Manager – Data Architecture

Senior Data Engineer

Data Engineer II

Principal Data Engineer

Lead Data Engineer

Staff Data Engineer

Senior Enterprise Architect, Enterprise Data Architect

Lead Director – Provider Data Engineering, Transformation

Data Architect

Senior Data Engineer – Senior Manager

Data Engineer – Experienced Associate

Senior Associate – Data Engineer

Senior Data Engineer – Manager