Python & Apache Spark Engineer / Data Processing Specialist

You will join a dynamic technology team responsible for designing, developing, and deploying innovative enterprise technology and AI-driven solutions supporting the delivery of tax services. The team combines expertise across software engineering, data engineering, AI, tax technology, change management, and project management. The projects cover the full technology lifecycle — from solution design and development through deployment and optimization, to training, adoption, and stakeholder engagement. You will work in a modern, cloud-based environment and contribute to the development of scalable data processing solutions, with a strong focus on Python, Apache Spark, cloud technologies, microservices, and modern data platforms.

• Strong analytical and problem-solving skills.
• Detail-oriented with the ability to identify technical issues and bottlenecks.
• Practical mindset balancing standardized processes with project flexibility.
• Strong organizational and time-management skills.
• Ability to independently manage workload, prioritize tasks, and meet tight deadlines.
• Excellent communication skills for both technical and non-technical stakeholders.
• Comfortable working independently and collaboratively in an international team.
• Willingness to take ownership and proactively advance technical topics.

Nice to have:

• Experience with Microsoft Azure or other major cloud platforms.
• Practical knowledge of Azure Service Bus, Azure Data Lake, Azure Blob Storage, Azure Redis, and other Azure SaaS/PaaS services.
• Experience building APIs and backend services with FastAPI.
• Hands-on experience with Docker.
• Experience with Kubernetes and container orchestration.
• Familiarity with modern AI/GenAI technologies including LangChain, LangGraph, RAG Pipelines, or LLM-based applications.
• Experience with Azure Synapse Analytics or Microsoft Fabric.
• Experience working in enterprise environments with complex data processing requirements.

Software & Data Engineering:

• Design, develop, and maintain robust, scalable, and production-ready Apache Spark applications.
• Develop efficient data processing, transformation, and analysis workflows using Python and Spark.
• Build solutions capable of handling large-scale datasets while maintaining high performance and reliability.
• Work with columnar data formats, particularly Parquet, and implement data solutions using Delta Tables.
• Develop clean, maintainable, testable, and efficient code following established engineering standards.
• Optimize Spark applications, data processing pipelines, and code for performance, scalability, and resource efficiency.
• Analyze and resolve technical issues affecting application reliability, performance, and data processing.
• Contribute to the design and implementation of scalable microservices-based solutions.

Technical Leadership & Code Quality:

• Define, promote, and enforce software engineering best practices and coding standards.
• Conduct detailed code reviews ensuring code quality, maintainability, security, performance, and compliance.
• Identify potential technical risks and proactively propose improvements.
• Support the team in solving complex technical and architectural problems.
• Provide technical guidance to team members and establish consistent development practices.
• Contribute to continuous improvement of development processes, workflows, and engineering standards.

Collaboration & Stakeholder Management:

• Work independently and collaboratively within a distributed, cross-functional team.
• Cooperate closely with software engineers, data specialists, architects, project managers, and business stakeholders.
• Communicate clearly, coordinate day-to-day technical activities, and help ensure smooth delivery.
• Maintain regular communication with clients and participate in technical discussions and project meetings.