Quick overview
SeniorityMid Senior
Work modeHybrid
LocationPlano, TX, United States
PostedYesterday
ScalaGitApache SparkAWSSnowflakeSplunkApacheDatabricksJavaJenkinsPythonRedshiftTerraformUnityGenerative AIData AnalysisZoomCI/CD
Job description
Duration: 7 Months Contract-to-Hire (RTH)
Openings: 2
Experience: 12+
Employment Type: Contract-to-Hire <>Job Description <>We are seeking an experienced Data & Cloud Services Engineer with 10+ years of hands-on cloud data engineering experience, specializing in AWS data lake technologies, Snowflake, Python, Terraform, and CI/CD. The ideal candidate will have experience building, maintaining, and deploying scalable cloud-based data solutions, along with familiarity with AI tools and agentic workflows. <>Required Skills
Openings: 2
Experience: 12+
Employment Type: Contract-to-Hire <>Job Description <>We are seeking an experienced Data & Cloud Services Engineer with 10+ years of hands-on cloud data engineering experience, specializing in AWS data lake technologies, Snowflake, Python, Terraform, and CI/CD. The ideal candidate will have experience building, maintaining, and deploying scalable cloud-based data solutions, along with familiarity with AI tools and agentic workflows. <>Required Skills
- 4–6 years of hands-on Cloud Data Engineering experience.
- Strong experience with AWS Glue, S3, Lambda, Step Functions, and Lake Formation.
- Hands-on experience with Snowflake, Python, Terraform, and CI/CD pipelines.
- Familiarity with AI tools and workflows, including GitHub Copilot, Claude, and Agentic AI workflows.
- Experience with AWS data lake architecture, data integration, and data processing.
- Knowledge of testing, release management, and deployment automation.
- Design, develop, and maintain scalable AWS cloud data engineering solutions.
- Build and manage data pipelines using AWS Glue, Lambda, Step Functions, and S3.
- Implement data movement and integration using Python APIs, AWS CLI, and Boto3.
- Support data analytics solutions using Athena, Redshift, EMR, and related AWS services.
- Develop and maintain infrastructure as code using Terraform.
- Implement and support CI/CD pipelines for AWS deployments.
- Monitor application performance, troubleshoot issues, and analyze logs using CloudWatch and Splunk.
- Collaborate with teams to improve data quality, automation, and cloud data platform reliability.
- Leverage AI-assisted development tools and agentic workflows to improve engineering productivity.
- Salesforce (SF) and Databricks.
- Apache Spark and Java/Scala.
- Control-M or other job scheduling tools.
- Bitbucket/Git, Jenkins, and ServiceNow.
- Snowflake Horizon Catalog and Databricks Unity Catalog.
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