Data Engineer - AWS

January 4

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Logo of Tiger Analytics

Tiger Analytics

Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.

Machine Learning β€’ Predictive Analytics β€’ Forecasting β€’ Optimization β€’ Natural Language Processing

1001 - 5000 employees

Founded 2011

πŸ€– Artificial Intelligence

🀝 B2B

πŸ“‹ Description

Tiger Analytics is a fast-growing advanced analytics consulting firm. β€’ As an AWS Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines on AWS cloud infrastructure. β€’ You will work closely with cross-functional teams to support data analytics, machine learning, and business intelligence initiatives. β€’ The ideal candidate will have strong experience with AWS services, Databricks, and Apache Airflow. β€’ Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc. β€’ Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements. β€’ Build and maintain orchestration workflows using Apache Airflow to automate data pipeline execution, scheduling, and monitoring. β€’ Optimize data pipelines for performance, reliability, and cost-effectiveness, leveraging AWS best practices and cloud-native technologies.

🎯 Requirements

β€’ 8+ years of experience building and deploying large-scale data processing pipelines in a production environment. β€’ Hands-on experience in designing and building data pipelines on AWS cloud infrastructure. β€’ Strong proficiency in AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc. β€’ Strong experience with Databricks and Apache Spark for data processing and analytics. β€’ Hands-on experience with Apache Airflow for orchestrating and scheduling data pipelines. β€’ Solid understanding of data modeling, database design principles, and SQL and Spark SQL. β€’ Experience with version control systems (e.g., Git) and CI/CD pipelines. β€’ Excellent communication skills and the ability to collaborate effectively with cross-functional teams. β€’ Strong problem-solving skills and attention to detail.

πŸ–οΈ Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

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