Data Engineer

• Provide technical leadership to data engineers, setting standards for solution design, coding practices, data governance, and quality.
• Define and evolve the enterprise data architecture leveraging Snowflake, Data Vault 2.0, and modern event driven and ELT frameworks.
• Lead architecture reviews, establish engineering best practices, and guide platform modernization efforts.
• Mentor engineering team members, facilitate code reviews, and promote continuous learning and innovation.
• Architect and oversee the delivery of scalable data pipelines, ingestion frameworks, and transformation processes using Snowflake, Python, Spark, Informatica (PowerCenter/IDMC), AWS Glue, and cloud-native tooling.
• Design and maintain enterprise data models, including Data Vault 2.0 (Hubs, Links, Satellites, PIT, Bridge structures) and dimensional models.
• Develop and optimize Snowflake platform capabilities, including: Snowpipe, Streams, Tasks, File Formats, External Stages Dynamic Tables and ELT pipeline automation Warehouse sizing, performance tuning, and cost optimization.
• Implement scalable batch, micro-batch, and real-time ingestion solutions following best practices.
• Translate complex business requirements into technical design specifications and actionable development plans.
• Partner with product owners, business stakeholders, architects, and analytics teams to deliver high-impact data solutions.
• Manage technical execution across multiple initiatives, ensuring alignment with enterprise priorities, data strategies, and delivery timelines.
• Oversee documentation, deployment readiness, testing processes, and quality assurance for production releases.
• Ensure operational reliability, data accuracy, and performance of enterprise data warehouse and analytical environments.
• Lead root-cause analysis for production issues and drive implementation of long-term preventative solutions. Implement robust monitoring frameworks using tools such as Snowflake Resource Monitors, CloudWatch, Datadog, or equivalent observability platforms.
• Conduct performance optimization on Snowflake workloads, SQL queries, pipelines, and integrations.

Senior Data Engineer

• Serve as the go-to subject matter expert on Salesforce Agentforce for internal teams and enterprise customers.
• Advise definitively on optimal use cases, implementation patterns.
• Act as an escalation point for critical or complex Agentforce project challenges.
• Lead the technical design and hands-on development of complex Agentforce solutions.
• Partner with customers and account teams to assess business challenges, identify high-impact Agentforce use cases.
• Lead and contribute to mentorship and enablement programs.
• Maintain a high degree of expertise on the rapidly evolving Agentforce product roadmap.
• Provide critical “Voice of the Customer” feedback to Product and Engineering organizations.
• Actively partner with GTM counterparts during pre-sales activities.

Senior AI and Data Architect

• 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, develop, and test tactical data communications software for multiple weapons systems.
• Design, develop, and test desktop and/or web-based graphical user interface solutions.
• Participate in all phases of the development lifecycle, from receipt of system requirements through support for final integration testing.
• Diagnose and resolve software issues

Junior/Mid-level Data Links Software Engineer

• 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

• 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

• Design, build, and optimize robust ETLs using PySpark and DBT to process large-scale customer datasets.
• Define the technical vision for DC data architecture, mentor engineers, and manage external contractors to ensure the team delivers high-quality, practical solutions for current and future needs.
• Partner with product, engineering, and applied science teams to scope work and deliver data solutions that address real-world challenges in customer data quality and product feature requirements.

Staff Software Engineer – DC Tech Lead

• Serve as a subject matter expert on HOPE’s data systems, business processes, workflows, and integration points.
• Design and implement robust data ingestion pipelines and ETL solutions for internal and external data sources.
• Manage all components of the Microsoft Azure ecosystem, including compute, storage, networking, databases, analytics, and governance.
• Ensure data loads and pipelines run reliably, with minimal impact on reporting and downstream systems.
• Lead data migration and conversion efforts for new software and system implementations.
• Lead, mentor, and develop a team of data professionals, fostering a culture of innovation, quality, and continuous improvement.
• Provide guidance on best practices for data management, data quality, analytics, and pipeline development.
• Collaborate with technology leaders, business partners, and cross‑functional teams to align data strategy and evaluate emerging tools and technologies.
• Partner with HOPE’s Learning & Development team to deliver end‑user training on reporting and data literacy.
• Oversee the use of statistical, analytical, and AI/ML methods to uncover insights, automate processes, and solve business challenges.
• Design and manage processes for data intake, validation, mining, engineering, modeling, visualization, and communication.
• Build Power BI dashboards and automated reporting solutions that address HOPE’s unique business needs.
• Recommend smart, data‑driven solutions that support organizational goals and operational efficiency.
• Ensure departmental milestones and goals are met within approved budgets.
• Partner with the Information Technology team to ensure proactive monitoring and timely system upgrades.
• Manage day‑to‑day staff performance, including timekeeping, capacity planning, and performance management.
• Perform other duties as assigned.

Manager, Data Architecture

• Serve as the functional DBA for Oracle and MongoDB across production and non‑production environments
• Partner with application teams on schema design, data modeling, and query optimization
• Analyze and resolve database-related functional issues, performance bottlenecks, and data anomalies
• Support release activities by validating database changes, scripts, and backward compatibility
• Provide guidance on transaction management, indexing strategy, and data access patterns
• Ensure data consistency, integrity, and correctness across applications and integrations
• Review and approve database changes for functional risk and impact
• Assist incident response by diagnosing database behavior and data-related failures
• Maintain functional documentation, standards, and runbooks for database usage

Data Engineer – Oracle, MongoDB DBA Specialist

• Lead a distributed engineering team across platform/product engineering, connectors, QA, DevOps/infra, AI implementation, data governance, and support.
• Own delivery, quality, release discipline, and execution of the technical roadmap.
• Install engineering discipline where it's thin: automated testing, QA, CI/CD, release governance, and versioning.
• Drive repeatable, perimeter-safe deployments, including containerization, infrastructure-as-code, secure deployment, and SOC 2 readiness.
• Partner with the Chief Architect on the connector framework, canonical metadata model, architecture decisions, and product IP.
• Build the team: assess current talent, retain the strong, hire the gaps, and align the team plan to the roadmap.
• Push practical AI use across coding, review, testing, ops, and engineering productivity.

Director of Engineering – Data Platform

• Partners with Regions Technology partners to Design, Build, and Maintain the data-based structures and systems in support of Data and Analytics and Data Product use cases
• Builds data pipelines to collect and arrange data and manage data storage in Regions’ big data environments
• Builds robust, testable programs for moving, transforming, and loading data using cloud-based Big Data tools such as Glue, Step-Functions, Snowflake, Kafka, and Sagemaker
• Designs and implements event-based architectures for streaming data
• Coordinates design and development with Data Products Partners, Data Scientists, Data Management, Data Modelers, and other technical partners to construct strategic and tactical data stores
• Provides consultation to all areas of the organization that plan to use data to make decisions
• Acts as trusted adviser and partner to business leaders; assisting in the identification of business needs & data opportunities

Senior Data Engineer – Cloud & AI Platform

• Develops, supports and implements data services for multiple applications to meet business objectives and user requirements
• Uses technical knowledge and industry experience to design, build and maintain technology solutions
• Works closely with users, developers, operations and business partners to define data service requirements and the data preparation process development
• Designs and builds data service infrastructure on multiple data platforms, according to key business processes and the overall workflow
• Develops and implements data solutions for multiple applications to ensure its scalability, availability and maintainability
• Implements data migration and transformation activities/processes to ensure the accuracy and security of data solutions

• 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 Solutions
• Build, maintain, and optimize data pipelines and workflows that support reporting, analytics, and business applications using SQL, Informatica, IICS, and Snowflake.
• Data Processing and Preparation
• Develop and manage data preparation routines for extracts, transformations, and reporting datasets, ensuring reliability and performance.
• Data Modeling and Optimization
• Create and maintain logical and physical data models following normalization principles and best practices.
• Tune queries for optimal performance across Snowflake and Oracle environments.
• Integration and Automation
• Work with various structured and semi-structured data formats (XML, JSON) and leverage AWS cloud frameworks for scalable data integration and processing.
• Data Security and Quality
• Ensure compliance with data security policies and implement best practices for data protection, integrity, and confidentiality.
• Collaboration and Leadership
• Partner with data analysts, developers, and business stakeholders to define data requirements, streamline processes, and improve data accessibility for reporting tools such as Power BI.
• Continuous Improvement
• Recommend and implement improvements to data architecture, workflows, and governance processes.
• Serve as a mentor to junior team members and promote a culture of curiosity and continuous learning.

• Designs, develops and optimizes highly complex, specialized data warehouses
• Analyzes business intelligence data and makes recommendations for growth and integration
• Works with IT and business customers to develop requirements for data warehouse architecture
• Provides support and guidance to ensure architecture aligns with BI application needs
• Leads and consults on implementation of data warehouses and ensures data integrity

Senior Data Architect – Retail Architecture

• Architecting, creating and maintaining data pipelines
• Assist with renovating the data management infrastructure to drive automation in data integration and management
• Work in partnership with data science teams and with business analysts in refining their data requirements
• Train counterparts across the organization in data pipelining and preparation techniques
• Work with data governance teams and participate in vetting and promoting content created in the business
• Demonstrated ability to communicate complex results to technical and non-technical audiences
• Work effectively in teams as well as independently across multiple tasks
• Strategic, intellectually curious thinker with focus on outcomes

Data Engineer jobs in Alabama

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Senior Data Engineer

Senior AI and Data Architect

Senior Software Engineer, Data

Senior Software Engineer, ERP, Data & Domain

Senior Data Engineer

Junior/Mid-level Data Links Software Engineer

Data Engineer

Data Engineer II

Staff Software Engineer – DC Tech Lead

Manager, Data Architecture

Data Engineer – Oracle, MongoDB DBA Specialist

Director of Engineering – Data Platform

Senior Data Engineer – Cloud & AI Platform

Data Engineer

Supply Chain Data Engineer

Senior Data Engineer

Senior Data Architect – Retail Architecture

Senior Data Engineer