Job description

Summary: Located in Arlington, VA, USA, our client’s Data & Analytics organization is seeking a technically strong Senior Software Development Engineer. The role involves contributing to the architecture, design, and development of scalable data platforms and data-intensive applications. It focuses on platforms that simplify secure external data exchange and enable product teams, consultants, and analysts to discover, access, and leverage enterprise data. The engineer will work across application, service, and data-processing layers using technologies such as Java/Spring Boot, React, TypeScript, Databricks, Spark, Hadoop, and related platforms. This role involves close collaboration with your immediate team as well as other development teams across programs to align on shared goals, contribute to cross-cutting initiatives, and deliver cohesive, enterprise-grade solutions. Responsibilities: • 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 to efficiently process, transform, and serve data. • Build features supporting enterprise data onboarding, exchange, discovery, and consumption. • Contribute to architecture and system design while collaborating with cross-functional teams to deliver scalable, high-quality solutions aligned with engineering best practices. • Write clean, maintainable, and efficient code using strong practices in testing, code reviews, and continuous improvement. • 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, stay current with technologies, and drive 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. Required Skills: • Data Engineering and Processing in Databricks/ Hadoop using Pyspark/ SQL. • Java (backend) React/TypeScript (frontend), CI/ CD, testing, and optimization. • Data Governance, security, and utilizing reusable frameworks. • Experience as a full-stack Software Engineer, with exposure to building platforms using modern technologies such as Java/Spring Boot, TypeScript, and React. • Experience building large-scale data platforms, distributed systems, and enterprise integration solutions across both 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 appropriate 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 working with data-intensive applications, including improving performance, scalability, and reliability across services and data-processing layers. • Strong collaboration and communication skills, with the ability to work effectively with cross-functional teams. • Curiosity, self-motivation, and a strong willingness to learn, with a growth mindset and interest in solving analytical, data-driven problems in an agile, fast-paced environment. Preferred Skills: • Master’s degree in computer science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience. Benefits: Details regarding benefits will be provided by the employer upon request.

Requirements

Must-haves

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 to efficiently process, transform, and serve data.
Build features supporting enterprise data onboarding, exchange, discovery, and consumption.
Contribute to architecture and system design while collaborating with cross-functional teams to deliver scalable, high-quality solutions aligned with engineering best practices.
Write clean, maintainable, and efficient code using strong practices in testing, code reviews, and continuous improvement.
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, stay current with technologies, and drive enhancements in quality, scalability, and developer productivity.
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) React/TypeScript (frontend), CI/ CD, testing, and optimization.
Data Governance, security, and utilizing reusable frameworks.
Experience as a full-stack Software Engineer, with exposure to building platforms using modern technologies such as Java/Spring Boot, TypeScript, and React.
Experience integrating AI driven capabilities into data platforms, with appropriate 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 working with data-intensive applications, including improving performance, scalability, and reliability across services and data-processing layers.
Strong collaboration and communication skills, with the ability to work effectively with cross-functional teams.
Curiosity, self-motivation, and a strong willingness to learn, with a growth mindset and interest in solving analytical, data-driven problems in an agile, fast-paced environment.

Nice-to-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

javareacttypescriptsqlaiapiagile

Platform: jobdiva
Effort: medium