Data Engineer

• 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

• 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 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

• 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

• Support data management, process, optimize and oversee quality controls for HEDIS reporting engine
• Work closely with IT, architect and engineer solutions for the Analytic Data Warehouse
• Assemble, test, process, and maintain the Analytic Discovery Platform
• Independently lead functional efforts for assigned projects with limited supervision
• Meet individually with customers for specific projects and attend with Intermediates for support

Senior Analytic Data Engineer

• Design and implement robust ETL/ELT pipelines
• Build and maintain Feature Stores and specialized datasets
• Develop the data pipelines required for Generative AI
• Act as the technical lead for our Snowflake data warehouse
• Manage complex, cross-platform data workflows using Airflow, Step Functions, or Azure Data Factory
• Partner directly with central IT, Database Administrators, and Security teams
• Implement automated validation and observability layers
• Drive the efficiency of our data stack by optimizing storage
• Work as a dedicated engineering partner to MLOps and Data Science teams

Data Engineer, AI

• Lead Storage and Data Migrations to AWS, Azure and Rackspace.
• Lead planning and execution of enterprise scale storage migrations with minimal downtime.
• Use tools including AWS DataSync, NetApp SnapMirror, Azure Data Box, Dell EMC XCP and vendor native replication technologies.
• Execute cutover planning, validation, and rollback procedures for clinical and enterprise workloads.
• Ensure migration activities align to resiliency, compliance and audit requirements.
• Partner with Cloud Architecture and Application teams to coordinate workload transitions and data validation.
• Own capacity, performance, lifecycle and daily operations of all storage hosted in Rackspace private cloud.
• Manage backup strategy, scheduling, and restore testing across on-premises, Rackspace, AWS and Azure workloads.
• Validate backup integrity, perform periodic restores and maintain compliance with retention policies.
• Engineer cloud native storage solutions including AWS S3, Azure Blob, Azure Data Lake.

Senior Storage and 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

• Develop, design, and implement data warehousing solutions.
• Collaborate with stakeholders to gather requirements
• Perform data analysis and reporting to support decision-making.
• Ensure data integrity and quality in data solutions.

Enterprise Data Warehouse Developer – Microsoft Fabric

• Design, develop, and maintain robust data processes and solutions to ensure the efficient movement and transformation of data across multiple systems
• Develop and maintain data models, databases, and data warehouses to support business intelligence and analytics needs
• Collaborate with stakeholders across IT, product, analytics, and business teams to gather requirements and provide data solutions that meet organizational needs
• Monitor work against production schedule, provide progress updates, and report any issues or technical difficulties to lead developers regularly
• Implement and manage data governance practices, ensuring data quality, integrity, and compliance with relevant regulations.
• Collaborate on the design and implementation of data security measures, including access controls, encryption, and data masking
• Mentor other associate and intermediate data engineers as needed
• Perform data analysis and provide insights to support decision-making across various departments
• Stay current with industry trends and emerging technologies in data engineering, recommending new tools and best practices as needed
• Other duties as assigned or requested.

Senior Data Engineer

• Design the vision and blueprint of the organization's data framework to support public health informatics objectives.
• Design and manage data systems, establishing policies for how data is stored, accessed, and governed.
• Coordinate various data sources within the organization to ensure consistency and integrity across the data environment.
• Integrate new data technologies into existing IT infrastructures.
• Perform data modeling and design activities to support reporting, analytics, and operational needs.
• Develop and maintain ETL pipelines to support data movement and transformation.
• Write and optimize SQL queries in support of data operations and system requirements.
• Administer database environments in coordination with application and infrastructure teams.
• Submit weekly status reports detailing completed and ongoing project activities, including risks as applicable.
• Maintain accurate records of work performed and hours expended in accordance with OTS Task Order requirements.

Data Architect

• 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

Data Engineer jobs in Louisiana

See all jobs on JobTailor