Senior Bigdata Engineer

Company Description Rysun Labs is a global AI, Data, and Digital innovation partner that helps enterprises and product startups accelerate their Data & AI strategies and digital transformation programs. The company focuses on enabling Fortune 2000 organizations to deliver exceptional customer experiences and intelligent operations, especially in High-tech, Retail & Ecommerce, and Energy sectors. Rysun collaborates closely with Microsoft, Google, and AWS to provide leading-edge enterprise technology solutions. With CMMI Level 5, ISO 9001, and ISO 27001 certifications, the organization operates with a strong quality-first mindset. Its collaborative culture connects teams across India, the USA, South Africa (as a Level 2 B-BBEE Contributor), and the UK, offering a dynamic, growth-oriented work environment.

Role Description This is a full-time, on-site Senior Bigdata Engineer role based in Ahmedabad. The Senior Bigdata Engineer will design, build, and maintain large-scale data pipelines and data processing frameworks to support advanced analytics and AI use cases. The role involves working with cross-functional teams to understand data requirements, model and optimize data flows, and ensure performance, scalability, and reliability of big data platforms. The engineer will be responsible for implementing data quality checks, security controls, and monitoring, as well as troubleshooting and optimizing existing data solutions. The position also includes mentoring junior engineers, contributing to best practices and standards, and collaborating with cloud architects to leverage services from providers such as Microsoft Azure, Google Cloud, and AWS.

Qualifications

• Strong big data engineering skills, including experience with distributed data processing frameworks (e.g., Apache Spark, Hadoop) and large-scale ETL / ELT pipelines.
• Proficiency with at least one major cloud platform (Azure, AWS, or Google Cloud) and hands-on experience with cloud-native data services (e.g., data lakes, data warehouses, streaming services).
• Solid knowledge of data modeling, SQL and NoSQL databases, and performance tuning for large datasets.
• Experience with data integration and streaming tools (e.g., Kafka, event hubs, message queues) and batch/orchestration frameworks (e.g., Airflow, Data Factory, Step Functions).
• Strong programming skills in languages commonly used for data engineering (such as Python, Scala, or Java), with a focus on clean, maintainable code and automation.
• Understanding of data governance, security, and compliance, including data quality, lineage, access control, and best practices for secure data handling.
• Ability to analyze complex data requirements, collaborate with data scientists and business stakeholders, and translate needs into scalable technical solutions.
• Experience mentoring or leading technical team members and contributing to architecture and