Must have strong knowledge on implementing metadata driven re-usable data ingestion, DQ framework, ETL pipeline design, ETL orchestration etc.
Expertise in building high-performing, scalable, enterprise-grade Data Lake/ Data Warehouse.
Solution/technical architecture in AWS on Data Lake /Datawarehouse/Lakehouse.
Required Skillset (Technical)
Must have implementation knowledge about different AWS services like: Step functions, Lambda, Glue Workflow, AWS S3, PostgreSQL, Terraform
Must have good knowledge on Data Like/DW/Lakehouse architecture. Good communication knowledge to participate in technical discussions with customers.
Must have knowledge and design experience on metadata driven re-usable ingestion and ETL framework
Must have hand-on knowledge on Python, Pyspark Must have hand on experience in POSTGRE sql
Candidate should also have knowledge on AWS SQS, Pub/Sub architecture, Kinesis Firehose, EKS etc.
Should have knowledge of AWS DevOpsGood-to-Have
AWS infrastructure, security
Knowledge of other AWS services like DMS, CloudTrail, CloudWatch, DynamoDB etc.
Knowledge about other ETL tools.
Experience on other cloud (e.g. Azure/GCP) implementation
Knowledge about Data Governance, Data Modelling etc.
Certified AWS Solutions Architect - Associate
Any Professional/Specialty AWS certification