Senior Full Stack Data Engineer

All IT Solutions is seeking a Senior Full Stack Data Engineer for a client engagement delivering scalable data platforms and data-intensive, analytics-driven applications across application, service, and data-processing layers. This contract role is hybrid in Arlington, VA, USA, with opportunities to collaborate with cross-functional teams, contribute to engineering best practices, and continuously grow as technologies evolve.

Responsibilities

• Contribute to the architecture, design, and development of scalable data platforms and data-intensive applications.
• Work across application, service, and data-processing layers using technologies such as Java/Spring Boot, React, TypeScript, Databricks, Spark, Hadoop, and related platforms.
• Collaborate within your immediate team and across development teams to align on shared goals, support cross-cutting initiatives, and deliver cohesive, enterprise-grade solutions.
• Participate in design and code reviews, contribute to engineering best practices, and support operational excellence.
• Work effectively across global time zones, help maintain a strong engineering culture, and continuously build technical skills while delivering reliable, high-quality software.
• Build full-stack features for business value, including capabilities that support data onboarding, exchange, discovery, and consumption.
• 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 processing, transformation, and serving of data.
• Identify and resolve performance bottlenecks across services, APIs, data-processing workloads, and user experience.
• Collaborate 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 and improve, staying current with technologies and driving enhancements 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 experience using Databricks / Hadoop with PySpark / SQL.
• Java (backend) plus React / TypeScript (frontend), along with CI/CD, testing, and optimization.
• Experience with Data Governance and security, including using reusable frameworks.
• Experience as a full-stack Software Engineer, with exposure to platforms built using modern technologies such as Java/Spring Boot, TypeScript, and React.
• Experience building large-scale data platforms and distributed systems, plus enterprise integration 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 focus on performance, scalability, and reliability across services and data-processing layers.
• Strong collaboration and communication skills to work effectively with cross-functional teams.
• Curiosity and self-motivation with a growth mindset, and willingness to learn while solving analytical, data-driven problems 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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