Data Cloud Consultant, AWS

Job Description: • Help customers shape their journey to adopting the cloud and provide our customers with technical and strategic guidance on their “cloud journey”. • Consult, plan, design, and implement Data solutions on the cloud customers • Design AWS Data Lake implementations • Design and Develop AWS Data Quality and Governance solutions • Become a deep technical resource that earns our customer's trust • Develop high-quality technical content such as automation tools, reference architectures, and white papers to help our customers build on the cloud • Innovate on behalf of customers and translate your thoughts into action yielding measurable results • Support solution development by conveying customer needs and feedback as input to technology roadmaps • Assist with technical briefs that document solutions and reference architecture implementations • Support internal and external brand development through thought leadership (blog posts, internal case studies) • AWS Data Architecture and Data Lake Implementation: assist with data collection, ingestion, catalog, storage and serving, VPC and S3 strategy, lambda architecture design, data catalog and serving layer guidance • Build Ingestion and Orchestration: design reusable ingestion frameworks, server-less approaches, monitoring, logging, alerting, retry capabilities, orchestration using AWS Glue, Step Functions, EMR, Batch, Lambda • Storage and Catalog: build bolthires S3 data lake storage approaches, buckets, prefixes, encryption, file types, partitioning, lifecycle management, cross-region replication if required Requirements: • Professional experience architecting/operating Data / DevOps solutions built on AWS • Experience in software/technology customer facing experience • You must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future. • Must Have: Apache Iceberg Sagemaker, SageMaker Lakehouse, SageMaker Catalog, Terraform • Should Have: bolthires, Redshift, EMR, Glue, DataBricks and/or Snowflake • Primary Languages - Python • Tooling, Services & Libraries – Airflow, Kafka, Parquet, Spark, Metaflow, Git, Hadoop • AWS Infrastructure Scripting – CloudFormation, AWS CLI, AWS CDK • Relevant AWS Services – S3, Lambda, Batch, RDS, DynamoDB, Redshift, Aurora, Neptune, VPC, CloudTrail, Service Catalog, bolthires, EMR, Kinesis, Glue, Lake Formation, Data Pipeline, IAM, Step Functions Benefits: • Work remotely • Full-time employee • Opportunities for thought leadership (write blog posts, develop internal case studies) • Emphasis on professional development and learning ('constantly learning' culture) • Equal opportunity employer Apply tot his job Apply tot his job