Data & Cloud Services Engineer

Sci Solutions Global•Plano, TX

14h

About The Position

The Data & Cloud Services Engineer will build and support AWS data lake solutions, Snowflake platforms, and Python-based data pipelines. The role also involves infrastructure automation, CI/CD, AWS deployments, and appropriate use of AI-assisted engineering tools to improve development productivity. The position is located in Plano, Texas. The client prefers candidates who are U.S. citizens, Green Card holders, or Green Card EAD holders. W2 employment is required; C2C, 1099, and third-party profiles are not accepted.

Requirements

At least 6 years of cloud data engineering experience.
Experience with AWS Glue, S3, Lambda, Step Functions, and Lake Formation.
Experience with Snowflake.
Experience with Python.
Experience with Terraform or other Infrastructure as Code.
Experience with CI/CD pipelines and AWS deployments.
Familiarity with AI-assisted tools such as GitHub Copilot, Claude, or agentic workflows.
Experience with data movement using AWS CLI, Python APIs, Spark, or Boto3.
Experience with analytics tools including Athena, S3 Select, EMR, or Redshift.
Experience with compute and storage using S3 or EC2.
Experience with CI/CD and change-management tools such as Bitbucket/Git, Jenkins, or ServiceNow.
Experience with monitoring tools such as AWS CloudWatch or Splunk.
W2 employment; C2C, 1099, and third-party profiles are not accepted.

Nice To Haves

Control-M scheduling experience.
Java or Scala programming experience.
Experience with Snowflake Horizon Catalog.
Experience with Databricks and Unity Catalog.
Additional experience with Spark and cloud data analytics.
U.S. citizenship, Green Card, or Green Card EAD work authorization is preferred.

Responsibilities

Build and support AWS data lake solutions, Snowflake platforms, and Python-based data pipelines.
Work with infrastructure automation and Infrastructure as Code.
Develop and support CI/CD pipelines and AWS deployments.
Use AI-assisted engineering tools appropriately to improve development productivity.

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