Data Engineer

2 weeks ago

Gurgaon, Haryana, India Honasa Consumer Ltd. Full time ₹ 9,00,000 - ₹ 12,00,000 per year

Key Responsibilities

  • Develop & Maintain Data Pipelines – Design, build, and optimize scalable ETL/ELT workflows to collect, transform, and store structured and unstructured data
  • Database & Query Optimization – Optimize SQL queries, ensure efficient data storage, and improve query performance for better system efficiency
  • Data Quality & Validation – Implement data quality checks and validation mechanisms to ensure data integrity and consistency across sources
  • Cloud & Data Warehousing – Work with Google Cloud Platform (GCP) (preferred) and data warehousing tools like BigQuery to manage large-scale datasets
  • Data Scraping & Processing – Utilize data scraping techniques to extract valuable insights from various web sources
  • Automation & Scheduling – Utilize Apache Airflow or similar ETL tools to automate data workflows and ensure smooth data processing
  • Collaboration – Work closely with data analysts, data scientists, and software engineers to understand data needs and optimize data architecture
  • Troubleshooting & Performance Tuning – Diagnose and resolve issues related to data pipelines, databases, and infrastructure

Requirements & Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related field
  • 1-2 years of experience in data engineering or a similar role
  • Strong proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL, etc.)
  • Hands-on experience with Python for data processing and automation
  • Knowledge of ETL processes and familiarity with Apache Airflow or similar workflow orchestration tools
  • Experience with data warehousing and cloud platforms, especially Google Cloud Platform (GCP) and BigQuery
  • Understanding of data modeling concepts and techniques
  • Knowledge of data scraping techniques and working with APIs for data extraction
  • Strong problem-solving and analytical skills to troubleshoot and optimize data systems
  • Excellent communication and collaboration skills to work in a team-driven environment

Nice-to-Have Skills (Preferred but Not Mandatory)

  • Familiarity with real-time data processing frameworks like Apache Kafka or Spark Streaming
  • Exposure to CI/CD pipelines and DevOps for data engineering workflows
  • Knowledge of Docker/Kubernetes for containerized data processing
  • Knowledge of Frontend/Backend scripting frameworks is an advantage

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