Senior data engineer

• To design, develop, and maintain large-scale data pipelines that can handle large datasets from multiple sources.
• Real-time data replication and batch processing of data using distributed computing platforms like Spark, Kafka, etc.
• To optimize the performance of data processing jobs and ensure system scalability and reliability.
• To collaborate with DevOps teams to manage infrastructure, including cloud environments like AWS.
• To collaborate with data scientists, analysts, and business stakeholders to develop tools and platforms that enable advanced analytics and reporting.

Requirements-

• Hands-on experience with AWS services such as S3, DMS, Lambda, EMR, Glue, Redshift, RDS (Postgres) Athena, Kinesics, etc.
• Expertise in data modeling and knowledge of modern file and table formats.
• Proficiency in programming languages such as Python, PySpark, and SQL/PLSQL for implementing data pipelines and ETL processes.
• Experience data architecting or deploying Cloud/Virtualization solutions (Like Data Lake, EDW, Mart ) in the enterprise.
• Cloud/hybrid cloud (preferably AWS) solution for data strategy for Data lake, BI and Analytics.

What is in for you-

• A stimulating working environment with equal employment opportunities.
• Growing of skills while working with industry leaders and top brands.
• A meritocratic culture with great career progression.