2 Honasa Consumer Jobs

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 (i.e., 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.