ob Summary

We are looking for a highly skilled Data Engineer with strong experience in designing, developing, and maintaining scalable data pipelines and modern data platforms. The candidate should have expertise in big data technologies, cloud platforms, ETL development, and data warehousing concepts.

The ideal candidate must be capable of handling large-scale structured and unstructured datasets while ensuring high data quality, reliability, security, and performance.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines.
• Build and optimize data architectures, data lakes, and data warehouses.
• Develop batch and real-time data processing solutions.
• Work closely with Data Scientists, Analysts, and Business Teams to support analytics requirements.
• Integrate data from multiple internal and external sources.
• Ensure data quality, governance, and security standards are maintained.
• Optimize SQL queries, data models, and pipeline performance.
• Automate workflows and monitoring processes.
• Troubleshoot data issues and provide long-term solutions.
• Participate in architecture discussions and technical design reviews.
• Support cloud migration and modernization initiatives.
• Maintain proper technical documentation and SOPs.

Required Skills & Experience

Mandatory Skills

• 6–7 years of experience as a Data Engineer.
• Strong experience in SQL and relational databases.
• Hands-on experience with ETL tools and data pipeline development.
• Experience with Python, Scala, or Java.
• Strong knowledge of data warehousing concepts.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with big data technologies:HadoopSparkHiveKafka
• Knowledge of orchestration tools such as Airflow.
• Experience with CI/CD pipelines and DevOps practices.
• Strong understanding of data modeling techniques.
• Experience handling large-scale datasets.

Preferred Skills

• Experience with Snowflake, Databricks, or Redshift.
• Knowledge of machine learning data pipelines.
• Experience in streaming technologies and real-time analytics.
• Understanding of security and compliance standards.
• Exposure to containerization tools such as Docker and Kubernetes.

Educational Qualification

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
• Relevant certifications in Cloud/Data Engineering will be an added advantage.