Data Engineer

Wissen Technology is Hiring for 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 are looking for a skilled Data Engineer II to join our Data Platform team. You will play a key role in building and optimizing our next-generation data infrastructure. Operating at the scale of Flipkart (Petabytes of data), you will design, develop, and maintain high-throughput distributed systems, bridging traditional big data engineering with modern cloud-native and AI-driven workflows.

Experience: 1- 5 years

Location: Bangalore

Mode of Work: Full time

Key Responsibilities:

• Design, develop, and maintain scalable ETL/ELT pipelines using Scala and Apache Spark/Flink (Batch & Streaming)
  
• Optimize Spark jobs and SQL queries for performance, efficiency, and cost
  
• Implement and manage Lakehouse architectures using Apache Iceberg, Hudi, or Delta Lake
  
• Apply Medallion Architecture (Bronze/Silver/Gold) for analytics and ML readiness
  
• Implement data quality checks and automated validation (Deequ, Great Expectations)
  
• Enable data observability for freshness, lineage, and reliability
  
• Deploy and manage workloads on GCP Dataproc and Kubernetes
  
• Contribute to infrastructure automation and IaC
  
• Collaborate with architects and product teams in an Agile/Scrum environment
  
• Participate in code reviews and enforce engineering best practices
  
• Explore GenAI and agentic workflows to improve data discovery and productivity
  
  
  

• 1–5 years of experience as a Data Engineer / Big Data Engineer
  
• Strong proficiency in Scala and Apache Spark (Batch & Streaming)
  
• Solid understanding of SQL and distributed computing concepts
  
• Experience with GCP (Dataproc, GCS, BigQuery) or equivalent cloud platforms (AWS/Azure)
  
• Hands-on experience with Docker and Kubernetes
  
• Experience with Lakehouse table formats (Iceberg, Hudi, Delta)
  
• Understanding of data warehousing and data modeling concepts
  
• Strong problem‑solving and communication skills
  
  

Good To Have Skills:

• Experience building data pipelines for ML / feature engineering
  
• Exposure to workflow orchestration tools (Airflow, Azkaban)
  
• Experience with real‑time analytics databases (Druid, ClickHouse, HBase)
  
• Knowledge of CI/CD pipelines for data applications
  
• Interest or experience in GenAI / AI‑driven data workflows
  
  

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: