Data Engineer

• Design and implement robust system architectures for real-time, near real-time, and batch processing data flows to meet the operational demands of complex business systems
• Master 'Vibe Coding' and AI-orchestrated development to accelerate the delivery of new data pipelines and GenAI applications, reducing the end-to-end development lifecycle from days to hours
• Design and deploy GenAI-powered 'Self-Service' tools, including automated documentation generators and natural language interfaces, to empower business users and reduce routine engineering requests
• Standardize AI-first engineering workflows across the team to ensure high-quality, auto-validated, and well-documented code delivery
• Develop and implement data transformations to enrich and provision data, following established specifications and standards while utilizing AI-first workflows
• Partner with data owners to ensure seamless, reliable data ingestion for both traditional analytics and GenAI-powered applications
• Collaborate with Data Architects, Operational Architects, and Data Analysts to understand the data and operational requirements across different business units
• Implement monitoring and CI/CD automation processes to track data quality and ensure the reliability of AI-supported data services

Senior Data Engineer

• Define and maintain the end-to-end application and data architecture
• Establish standards for system design, integration patterns (APIs, middleware, eventing), and data models
• Ensure scalability, performance, and long-term maintainability
• Act as the technical lead across all external development partners
• Review and approve solution designs, code architecture, and technical approaches
• Challenge vendors where needed — no rubber stamping
• Ensure delivery aligns with architectural standards and business outcomes
• Define and oversee data architecture, governance, and quality standards
• Manage integration across systems (ERP, CRM, eCommerce, etc.)
• Ensure data is usable, reliable, and decision-ready
• Partner with leadership to translate business goals into technical roadmaps and system requirements
• Simplify complex technical concepts for non-technical stakeholders
• Evaluate and guide decisions on SaaS vs. custom development, build vs. buy vs. integrate
• Design integration architecture across ERP, marketing systems, and data platforms
• Establish architecture governance processes
• Participate in sprint reviews, backlog prioritization, and delivery checkpoints
• Ensure proper documentation, testing, and deployment standards

Application & Data Architect

• Create and maintain optimal data pipeline architecture.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Strong communication needed.
• Keep our data separated and secure across national boundaries through multiple data centers and Azure regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.

• Design, build, document and maintain data pipelines to support our Data Warehouse and our Data Acquisition (IoT data) systems.
• Uphold and contribute to the creation of standards for quality and security.
• Collaborate with cross-functional teams to enhance our data capabilities, supporting our mission to build a more sustainable future through innovative technology and exceptional customer experience.

• Support cloud-based data pipelines for ingestion, transformation, and storage.
• Work with AWS services to help maintain and improve data workflows.
• Help with data validation, monitoring, and troubleshooting of analytics pipelines.
• Contribute to data lake solutions used for reporting and analytics.
• Support reporting and visualization tools used by business partners.
• Follow best practices for source control, documentation, and team collaboration.

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Senior Data Engineer

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