Senior Full Stack Data Engineer

All IT Solutions is supporting a client engagement for a Senior Full Stack Data Engineer role based in Arlington, VA, USA (hybrid). This position focuses on scalable data platforms and data-intensive, analytics-driven applications spanning application, service, and data-processing layers.

The work combines full-stack development with data engineering to deliver enterprise-grade solutions, including performance tuning, operational support, and collaboration across teams and stakeholders across global time zones.

Key Responsibilities

• Contribute to the architecture, design, and development of scalable data platforms and data-intensive applications.
• Develop across application, service, and data-processing layers using technologies including Java/Spring Boot, React, TypeScript, Databricks, Spark, Hadoop, and related platforms.
• Collaborate with your immediate team and other development teams to align on shared goals, support cross-cutting initiatives, and deliver cohesive enterprise-grade outcomes.
• Participate in design and code reviews, contribute to engineering best practices, and help drive operational excellence.
• Work effectively across global time zones, support a strong engineering culture, and continuously build technical skills while delivering reliable, high-quality software.
• Build innovative products that help businesses unlock more value from their data.
• Develop full-stack, data-intensive, analytics-driven applications that support business experimentation and decision-making for large organizations.
• Design, build, and maintain scalable data platforms, distributed systems, and enterprise integration solutions across on-premises and cloud environments.
• Develop and optimize data-intensive applications using Databricks, Spark, and related platforms for efficient data processing, transformation, and serving.
• Build features supporting enterprise data onboarding, exchange, discovery, and consumption.
• Contribute to architecture and system design with cross-functional teams to deliver scalable, high-quality solutions aligned with best practices.
• Write clean, maintainable, and efficient code using testing, code reviews, and continuous improvement practices.
• Identify and resolve performance bottlenecks across services, APIs, data-processing workloads, and user experience.
• Partner with Product, Engineering, Data Governance, Security, and business stakeholders to understand and deliver requirements.
• Mentor and support team members while contributing to a collaborative, growth-oriented engineering culture.
• Continuously learn, stay current with technologies, and drive improvements in quality, scalability, and developer productivity.

Requirements

• Bachelor’s degree in computer science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience
• Data Engineering and Processing in Databricks/Hadoop using PySpark/SQL
• Java (backend) plus React/TypeScript (frontend), with CI/CD, testing, and optimization experience
• Experience related to Data Governance and security, including utilizing reusable frameworks
• Experience as a full-stack Software Engineer, including exposure to building platforms with Java/Spring Boot, TypeScript, and React
• Experience building large-scale data platforms, distributed systems, and enterprise integration solutions across on-premises and cloud environments, leveraging technologies such as Spark, Kafka, Flink, NiFi, Hadoop/Cloudera, Databricks, and modern cloud-native data services
• Experience integrating AI driven capabilities into data platforms with governance and guardrails for emerging use cases, including agentic commerce
• Experience building reusable platforms that serve multiple products, teams, or business domains
• Foundational understanding of software engineering principles, including object-oriented programming, API design, and scalable system design
• Interest in data-intensive applications, with a focus on improving performance, scalability, and reliability across services and data-processing layers
• Strong collaboration and communication skills for cross-functional teamwork
• Curiosity, self-motivation, and willingness to learn in an agile, fast-paced environment

Preferred Qualifications

• Master’s degree in computer science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience

Technologies

• Java, Spring Boot, React, TypeScript
• Databricks, Spark, Hadoop, PySpark, SQL
• CI/CD
• Kafka, Flink, NiFi
• Hadoop/Cloudera, Cloudera
• Cloud-native data services

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Job Type: Contract

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