Accenture AWS ML Engineering Consultant in Boston, Massachusetts
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A data engineering professional who thrives in a team setting where you can turn your prodigious creative and analytical powers to obliterating problems. Your superpower Building and delivering solutions to help our clients meet the soaring demands of AI and machine learning, IoT, advanced analytics, open source and other emerging digital technologies. You have top-notch communication and people skills.
Assess the full technology stack of services needed in delivering data and analytic solutions, including operations management and automation
Make your own decisions to define solutions and ask for guidance on complex problems
Apply methodology, reusable assets, and previous work experience so that your work is always of high quality
Compare alternative solutions from technical and business perspectives to support the defined cost and service requirements
Keep up to speed on new and emerging technologies/patterns/methodologies and products that will be of interest to our clients
Here’s what you need:
Bachelor's degree in Computer Science, Engineering, Technical Science or equivalent (minimum 12 years) work experience
Minimum 2 years of hands-on development on AWS in designing and deploying solutions on AWS platform and experience in workload migrations, including hands-on experience implementing data engineering and data processing using AWS services: Glue, Lambda, Kinesis, Kafka, Redshift, RDS, Aurora, Neptune, DynamoDB, CloudWatch, ECS, Docker and/or API Gateway.
Minimum 3 years of hands-on Python coding, knowledge & experience along with Spark/Scala, PySpark, Boto3 and/or AWS SDK and as well as experience in big data analytics, information analysis, database management, microservices, and DevOps, working with SQL.
Minimum 2 years’ experience with SageMaker Model Monitor, SageMaker Model Registry, SageMaker Studio and SageMaker Pipelines
Bonus points if you have:
Certified AWS Developer - Associate
Certified AWS Data Analytics Specialty
Certified AWS ML Specialty
DevOps on an AWS platform. Multi-cloud experience a plus.
Experience developing and deploying ETL solutions on AWS
Multi-cloud experience a plus - Azure, AWS, Google
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