Qualifications

• 5-7 years of hands-on experience with Python, focusing on data engineering and application development.
• Extensive knowledge of AWS cloud services including S3, EMR, Glue, Lambda, IAM, EC2, ECS/EKS, CloudWatch, and Redshift.
• Proficiency in Apache Spark for large-scale batch processing and Apache Flink for real-time data streaming.
• Solid understanding of data modeling, warehousing, and lakehouse concepts.
• Experience with ETL/ELT frameworks, data integration, and both relational and NoSQL databases.
• Familiarity with distributed computing and big data technologies, along with Docker and Kubernetes expertise.
• Strong SQL skills and experience with Git and Agile development methodologies.

Responsibilities

• Design and implement scalable and secure data architectures on AWS.
• Build and optimize batch processing pipelines using Apache Spark.
• Develop real-time streaming data solutions with Apache Flink.
• Create end-to-end data ingestion, transformation, and processing pipelines.
• Define data models, governance standards, and architectural best practices.
• Coordinate and manage data integration tasks using ETL/ELT methodologies.
• Ensure the use of industry standards for big data technologies in project implementations.

Benefits

• Opportunities for continued professional development and skill enhancement.
• Flexible working arrangements to accommodate work-life balance.
• Access to cutting-edge technology tools and resources for project execution.
• Collaborative work environment encouraging innovative ideas and teamwork.
• Health and wellness programs to support employee well-being.