Job Description

Location: Bangalore (Hybrid)
Experience: 610 years
Type: Full-time
What Were Looking For
Our client KJBN Labs is looking for a Senior Data Engineer who thrives in building scalable data pipelines and is passionate about transforming raw data into meaningful insights. You should have hands-on experience handling large-scale data, automating ETL workflows, and working with modern data lake/lakehouse architectures. Experience in Apache Hop for orchestrating and managing data workflows will be a strong advantage.
Key Responsibilities

• Design, develop, and optimize ETL pipelines using Spark, Python, Apache Hop, and modern data engineering tools.
• Work with data lakes/lakehouses (Delta Lake, Apache Iceberg, etc.) to manage and process structured and semi-structured data.
• Ensure high-quality data ingestion, transformation, and validation processes.
• Optimize pipelines to handle millions of records/day with high reliability and performance.
• Collaborate with analysts, data scientists, and product teams to understand data needs and build reusable data models.
• Monitor, debug, and enhance workflows with robust error handling and logging.
• Work with complex datasets across domains like customer behavior, real-time logs, transactions, or sensor data.
• Use orchestration tools like Apache Hop to manage and automate data pipelines and workflows.
• Design and optimize scalable, secure data pipelines and storage solutions (data lakes, warehouses), integrating structured and unstructured data from diverse sources.
• Ensure system performance, cost-efficiency, and compliance through automation, best practices, and data governance policies.
• Collaborate with cross-functional teams to support analytics and ML needs, while mentoring junior engineers and resolving complex data issues.

Key Skills & Technologies

• Strong programming skills in Python
• Deep experience with ETL development and Spark (PySpark/Scala)
• Hands-on experience working with Data Lake or Lakehouse architectures (S3 + Delta Lake, Iceberg, Hudi, etc.)
• Familiarity with streaming data and batch processing
• Experience using Apache Hop for data orchestration and workflow management
• Experience working with large volumes (e.g., 100M+ rows/day) of diverse datasets
• Bonus: Exposure to Rust is a plus but not mandatory

Why Join KJBN?

• Work on impactful, large-scale data systems powering real business outcomes
• Collaborate with a high-performing data team
• Flexible work environment with opportunities for ownership and innovation

Ready to build the future of data infrastructure with us? Apply now!