Lead Data Engineer

Wissen Technology is Hiring for Lead Data Engineer  

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 : We’re looking for a Lead Data Engineer with strong hands-on expertise in PySpark, real-time data processing, and the Microsoft Azure ecosystem. You’ll architect and develop large-scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems.  

This is a hands-on leadership role where you’ll design, optimize, and scale a modern data platform that drives analytics and operational insights enterprise wide.  

Experience: 7- 12 Years  

Location: Bangalore  

Mode of Work: Full Time  

Key Responsibilities:  

• Design and implement large-scale data pipelines using PySpark, Azure Databricks, and Microsoft Fabric  
  
• Handle and process massive volumes of real-time data from diverse, high-velocity sources  
  
• Build and optimize real-time and batch ingestion frameworks for structured and semi-structured data  
  
• Develop event-driven architectures using Azure Functions, Event Hub, and Data Factory  
  
• Implement Medallion architecture (Bronze/Silver/Gold) and strong data validation frameworks  
  
• Ensure pipeline scalability, performance tuning, and fault tolerance for high-throughput workloads  
  
• Enforce data governance, lineage, and security across all data layers  
  
• Build CI/CD pipelines and implement observability for data workflows  
  
• Mentor a team of data engineers and drive engineering best practices  
  

Requirements:  

• 7+ years in Data Engineering, including 3+ years in a lead or architecture role  
  
• Proven expertise in PySpark and Python for large-scale data processing  
  
• Hands-on experience processing massive real-time data streams in production environments  
  
• Strong proficiency in Microsoft Azure, including:  
  
• Azure Databricks, Microsoft Fabric, Data Factory, Event Hub / Service Bus  
  
• Delta Lake on ADLS Gen2  
  
• Advanced knowledge of SQL, data modeling, schema evolution, and data quality frameworks combined with design and architecture skills  
  
• Experience building event-driven, serverless data architectures  
  
• Strong understanding of data privacy, lineage, and governance principles  
  

Good To Have Sk ills:  

• Domain expertise in financial services  
  
• Familiarity with Microsoft Purview, Azure Monitor, and Key Vault  
  
• Pre-sales experience desirable  
  

Wissen Sites:  

Website: www.wissen.com      

LinkedIn: https://www.linkedin.com/company/wissen - technology      

Wissen Leadership: https://www.wissen.com/company/leadership - team/      

Wissen Live: https://www.linkedin.com/company/wissen - technology/posts/feedView=All      
Wissen Thought Leadership: https://www.wissen.com/articles/