Lead Data Engineer - ETL / Python

Description : About The Role :

We are seeking a highly skilled and experienced Senior / Lead Data Engineer to design, develop, and maintain scalable, reliable, and efficient data pipelines and ETL solutions.

The role requires strong expertise across multi-cloud environments, modern data warehousing platforms, programming languages, and data orchestration tools.

You will play a pivotal role in transforming raw data into actionable insights, ensuring data quality, and enabling analytics and reporting initiatives across the :

• Design, build, and optimize complex ETL / ELT data pipelines using Python, PySpark, Scala, and advanced SQL.
• Implement and manage ETL processes using Informatica PowerCenter, Databricks, AWS Glue, and Snowflake.
• Develop and deploy scalable data solutions across AWS, Azure, GCP, and Microsoft Fabric using cloud-native services.
• Manage and optimize databases, including Redshift, SQL Server, and AWS RDS.
• Orchestrate and monitor data workflows with Apache Airflow to ensure reliable and timely delivery.
• Implement streaming solutions with Apache Kafka and containerized services with Kubernetes.
• Automate data workflows and system monitoring using Unix shell scripting.
• Apply CI / CD practices to data pipelines and enforce Data Cleanroom principles for privacy-compliant collaboration.
• Collaborate with BI / reporting teams to deliver optimized datasets for Tableau, Looker, and Power BI.
• Troubleshoot and resolve performance issues in pipelines and database queries.
• Maintain detailed technical documentation and collaborate closely with cross-functional Bachelor's or master's degree in Computer Science, Engineering, Information Technology, or a related field.
• Experience : 5+ years for Senior Data Engineer, 8+ years for Lead Data Engineer.
• Languages : Proficiency in SQL, Python (including PySpark), Scala, and Unix Shell Scripting.
• ETL Tools : Hands-on experience with Informatica PowerCenter, Databricks, and AWS Glue.
• Data Warehousing : Expertise in Snowflake and Redshift.
• Cloud Platforms : Strong exposure to at least two of AWS, Azure, and GCP; familiarity with Microsoft Fabric.
• Databases : Solid knowledge of Redshift, SQL Server, and AWS RDS.
• Orchestration : Proven experience with Apache Airflow.
• Streaming Containerization : Practical experience with Apache Kafka and Kubernetes.
• Concepts : Working knowledge of CI / CD pipelines and Data Cleanroom practices.
• Reporting Tools : Understanding of data provisioning for Tableau, Looker, or Power BI.
• Strong problem-solving skills, communication ability, and a proactive approach to emerging technologies.

(ref : hirist.tech)