5-7 years of experience as a full-stack Software Engineer with a focus on modern technologies like Java/Spring Boot, TypeScript, and React.
Hands-on experience with data engineering and processing tools like Databricks, Spark, and Hadoop/Cloudera.
Proven ability to design, build, and maintain scalable data platforms and distributed systems in both on-premises and cloud settings.
Expertise in developing data-intensive applications and optimizing performance for maximum efficiency and reliability.
Familiarity with CI/CD practices, software testing, and code review processes to ensure quality and maintainability.
Strong foundational understanding of software engineering principles, including API design and scalable system architecture.
Effective collaboration and communication skills to work with diverse teams across global time zones.
Responsibilities
Design and maintain scalable data platforms and distributed systems for both cloud and on-premises environments.
Develop and optimize applications using Databricks and Spark for efficient data processing and transformation.
Implement features that facilitate enterprise data onboarding, exchange, and consumption.
Collaborate with cross-functional teams to ensure high-quality, scalable solutions aligned with engineering best practices.
Write clean, maintainable code while actively participating in testing and code reviews.
Identify performance bottlenecks and implement resolutions across services and applications.
Mentor team members and contribute to a culture of collaboration and learning.
Benefits
Opportunity to work with cutting-edge technologies and data platforms.
Collaborative and growth-oriented engineering culture.
Ongoing learning and career development opportunities.
Exposure to cross-functional teams and global stakeholders.
Flexible work environment and agile engineering practices.
Full Job Description
Overview:
The Client's Data & Analytics organization is seeking a technically strong Senior Software Development Engineer to contribute to the architecture, design, and development of scalable data platforms and data-intensive applications.
The role focuses on platforms that simplify secure external data exchange and enable product teams, consultants, and analysts to Client, 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.
The role involves close collaboration with development teams and cross-functional stakeholders to align on shared goals, contribute to cross-cutting initiatives, and deliver cohesive, enterprise-grade solutions.
The engineer will participate in architecture, design, and code reviews; apply strong practices in testing, continuous improvement, data governance, and security; and support operational excellence.
The position requires a collaborative, technically strong approach, a willingness to continuously learn, and the ability to contribute to reliable, scalable, high-quality software in a fast-paced, agile engineering environment.
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.
Required Education:
Bachelors or master's degree in computer science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.
Required Skills, Experience, & Abilities:
Experience as a full-stack Software Engineer building platforms with modern technologies such as Java/Spring Boot, TypeScript, and React.
Experience with data engineering and processing using Databricks, Spark, Hadoop/Cloudera, PySpark, and SQL.
Experience designing, building, and maintaining scalable data platforms, distributed systems, and enterprise integration solutions across on-premises and cloud environments.
Experience developing data-intensive applications and optimizing data-processing workloads for performance, scalability, and reliability.
Experience with CI/CD, software testing, code reviews, and engineering best practices.
Foundational understanding of software engineering principles, including object-oriented programming, API design, and scalable system design.
bility to collaborate effectively with Product, Engineering, Data Governance, Security, business stakeholders, and cross-functional teams.
Strong collaboration and communication skills, with the ability to work effectively across global time zones.
bility to write clean, maintainable, and efficient code and contribute to architecture and system design.
bility to identify and resolve performance bottlenecks across services, APIs, data-processing workloads, and user experience.
bility to build reusable platforms and frameworks that serve multiple products, teams, or business domains.
Desired Skills, Experience, & Abilities:
Experience with Kafka, Flink, NiFi, 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 with data governance, security, and reusable engineering frameworks.
Experience building features that support enterprise data onboarding, secure data exchange, discovery, and consumption.
Interest in data-intensive applications and improving performance, scalability, and reliability across services and data-processing layers.
Experience mentoring and supporting team members while contributing to a collaborative, growth-oriented engineering culture.
Curiosity, self-motivation, willingness to learn, and a growth mindset.
Interest in solving analytical, data-driven problems in an agile, fast-paced engineering environment.
