Data Engineer

Overview

Job Title: Data Engineer

Experience: 5–8 Years

Location:

Pune
Shift Timings: 2 PM – 11 PM IST
Notice Period: Immediate Joiners Only
Job Summary

We are seeking an experienced Data Engineer with 5–8 years of expertise in designing, building, and optimizing scalable data pipelines and working with large datasets. The ideal candidate should have strong skills in backend technologies, microservices, and cloud-based data platforms. Experience or exposure to LLMs, AI-driven applications, or Whiz AI is a strong advantage. A product-oriented mindset and ability to thrive in fast-paced engineering environments are essential.

Key Responsibilities

• Design, build, and maintain scalable, reliable, and high-performance data pipelines.
  
• Work with large datasets across structured, semi-structured, and unstructured data sources.
  
• Develop and maintain data ingestion, transformation (ETL/ELT), and validation workflows.
  
• Build backend components and services that support data processing and analytical workloads.
  
• Collaborate with engineering, product, and data science teams to support product features and data-driven initiatives.
  
• Optimize data models, query performance, and storage solutions for efficiency and scalability.
  
• Work with microservices architectures and integrate data flows across distributed systems.
  
• Utilize cloud-native tools (AWS/Azure/GCP) for data engineering, orchestration, and deployment.
  
• Implement data quality checks, monitoring, and alerting processes to ensure accuracy and reliability.
  
• Contribute to AI/LLM-driven data workflows, including preparation of clean, structured datasets.
  
• Maintain documentation, coding standards, and best practices across the data engineering lifecycle.
  

Required Skills & Experience

• 5–8 years of hands-on experience in data engineering.
  
• Strong proficiency in Python/Java/Scala .
  
• Proven experience in building data pipelines, ETL/ELT workflows, and distributed data processing.
  
• Experience with cloud platforms such as AWS, Azure, or GCP.
  
• Strong knowledge of SQL and NoSQL databases.
  
• Understanding of microservices architecture and API-driven development.
  
• Experience with tools/frameworks like Spark, Kafka, Airflow, DBT, or similar.
  
• Strong debugging, problem-solving, and performance optimization skills.
  
• Excellent communication and collaboration abilities.
  
• Product-focused and comfortable working in fast-paced engineering environments.
  

Good to Have (Not Mandatory)

• Exposure to LLMs, AI/ML workflows, or platforms like Whiz AI.
  
• Experience with data preparation for AI/ML model training.
  
• Knowledge of containerized and orchestrated environments (Docker, Kubernetes).
  
• Familiarity with DevOps practices and CI/CD pipelines.