in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages such as Python, Java, and SQL. Strong knowledge of data warehousing, data lakes, and data lakehouse architectures. Excellent analytical and More ❯
able to work across full data cycle. - Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD - Coding experience in Apache Spark, Iceberg or Python (Pandas) - Experience in change and release management. - Experience in Database Warehouse design and data modelling - Experience managing Data Migration projects. - Cloud data platform development and … the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB - Good experience with DBT, Apache Iceberg, Docker, Microsoft BI stack (nice to have) - Experience in data warehouse design (Kimball and lake house, medallion and data vault) is a definite preference as is knowledge of More ❯
able to work across full data cycle. Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD Coding experience in Apache Spark, Iceberg or Python (Pandas) Experience in change and release management. Experience in Database Warehouse design and data modelling Experience managing Data Migration projects. Cloud data platform development and … the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB Good experience with DBT, Apache Iceberg, Docker, Microsoft BI stack (nice to have) Experience in data warehouse design (Kimball and lake house, medallion and data vault) is a definite preference as is knowledge of More ❯
