Data Engineer

Wissen Technology is Hiring for

About Wissen Technology:

At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, cutting-edge technology expertise, and a relentless focus on quality. We don’t just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provide clients with the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent. Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.

Job Summary

Experience:

Location:

Mode of Work

Key

• Design, develop, and maintain data pipelines and ETL workflows using Python and Pandas.
  
• Implement, schedule, and monitor workflows using Apache Airflow.
  
• Work with Azure Cloud Services to manage data storage, processing, and orchestration.
  
• Collaborate with data scientists, analysts, and business teams to understand requirements and deliver reliable data solutions.
  
• Ensure data quality, accuracy, and consistency across multiple data sources.
  
• Optimize existing data pipelines for scalability and performance.
  
• Participate in troubleshooting, root cause analysis, and process improvements.
  
• Maintain comprehensive documentation of data processes and systems.
  

Requirements:

• 4–7 years of hands-on experience in Data Engineering or a similar role.
  
• Strong programming experience in Python (mandatory).
  
• Proficiency with Pandas for data manipulation and transformation (mandatory).
  
• Expertise in Airflow for workflow orchestration (mandatory).
  
• Experience working with Azure Cloud Services for data storage and compute.
  
• Solid understanding of ETL/ELT processes, data modeling, and data lifecycle management.
  
• Excellent analytical and problem-solving abilities.
  
• Strong communication and collaboration skills.
  

• Experience with PySpark for distributed data processing.
  
• Familiarity with Kubernetes for container orchestration and workflow management.
  
• Exposure to data warehousing and data lake architectures.
  
• Knowledge of CI/CD pipelines and data infrastructure automation.
  

Wissen Sites: