Data Engineer

Job Purpose The Data Engineer IV is responsible for designing, developing, and optimizing enterprise data integration solutions and cloud-based data platforms that support analytics, AI, and operational business processes. This role serves as a senior technical contributor, driving architecture decisions, establishing engineering standards, and delivering scalable, secure, and automated data solutions across the organization. The position plays a key role in building and evolving Data Integration as a Service (DIaaS) capabilities through reusable frameworks, API‑driven integrations, event‑based architectures, and cloud‑native platforms that enable efficient and reliable data movement across enterprise systems. Key Responsibilities Platform Architecture & Engineering Design and implement scalable cloud‑based data platforms and integration architectures. Develop enterprise‑grade data ingestion, transformation, orchestration, and delivery pipelines. Architect and implement API‑driven, event‑based, and batch integration solutions supporting operational and analytical workloads. Define technical standards and best practices for data modeling, integration design, data quality, and interoperability. Support bi‑directional data integration patterns that enable insights and metrics to flow between analytical and operational platforms. Evaluate and recommend emerging technologies, tools, and architectural patterns to improve platform capabilities. Data Integration & Automation Develop and maintain reusable integration frameworks, APIs, connectors, and automation components. Build and support CI/CD pipelines and Infrastructure‑as‑Code solutions for data and integration platforms. Implement observability capabilities including monitoring, lineage, validation, reconciliation, logging, and alerting. Establish API governance, schema standards, contract testing, and integration best practices. Optimize platform performance, reliability, scalability, and cloud resource utilization. Technical Leadership & Collaboration Provide technical leadership and guidance for complex data integration and platform initiatives. Collaborate with architects, engineers, security teams, cloud teams, and business stakeholders to deliver high‑quality solutions. Lead architecture reviews, technical design sessions, and solution assessments. Mentor junior and mid‑level engineers on engineering standards, architecture principles, and development best practices. Support troubleshooting and resolution of complex platforms, integration, and data engineering challenges. Job Requirements Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field. 7+ years of experience in data engineering, data integration, platform engineering, or solution architecture roles. Strong hands‑on experience designing and implementing cloud‑based data and integration platforms. Expertise in ETL/ELT development, API integrations, event‑driven architectures, and distributed data processing. Experience implementing CI/CD pipelines, Infrastructure‑as‑Code, and DevOps practices. Strong experience with technologies such as Snowflake, Python, Kafka, Airflow, Azure Data Factory, AWS Glue, Informatica, Databricks or similar platforms. Knowledge of cloud platforms including AWS, Azure, and Google Cloud Platform. Experience with data governance, metadata management, security, and compliance requirements. Strong analytical, problem‑solving, communication, and stakeholder collaboration skills. Preferred Qualifications Experience with Data Mesh, Lakehouse architecture, Master Data Management (MDM), or real‑time streaming platforms. Familiarity with AI/ML data pipelines and MLOps frameworks. Cloud certifications in AWS, Azure, or Google Cloud Platform. Experience implementing enterprise‑scale integration platforms and self‑service data capabilities. Compensation/Benefits Competitive compensation Full health benefits – Medical/Dental/Vision 401(k) match DTO (discretionary time off) Health savings account (HSA) with company contribution College tuition reimbursement program (STEM degrees) Unlimited use of LinkedIn Learning Success Measures Reliable and scalable integration platform delivery. Improved data quality, observability, and operational efficiency. Increased automation and developer productivity through reusable frameworks. Successful implementation of cloud‑native architecture and integration standards. Timely delivery of high‑impact data and integration solutions aligned with business objectives. SPONSORSHIP Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time. Upbound Group is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. #J-18808-Ljbffr