Job description

Job Description: • Hands-on experience with one or more AWS data lake technologies: • Data Lake: AWS Lake Formation, AWS Glue, AWS Step Function, AWS Lambda • Data Movement: AWS CLI, Python API, Spark, Python Boto3 • Data Analytics: AWS Athena, S3 Select, EMR, Redshift • Compute/Storage: AWS S3, AWS EC2 • Knowledge of at least one scheduling tool, Control-M Preferred • Working experience in one or more of the following languages: Python (Preferred),Java/Scala (Good to Have) • Knowledge and experience with testing, releasing, and CI/CD pipeline deployments into AWS using: • Tools: Bitbucket/Git, Jenkins, Service Now • Log Trace: AWS CloudWatch, Splunk. Knowledge on Snowflake - Horizon Catalog and Databricks - Unity Catalog is a huge plus. Must have: • Minimum 6 years of experience of cloud data engineering • Glue, S3, Lambda, Step function, Lake Formation, Snowflake, Python, and Terraform, CI/CD • Conversant with AI Suite (Copilot/Claude/Agentic workflows) Nice to have: • SF and Databricks Additional Skills: • Glue, S3, Lambda, Step function, Lake Formation, Snowflake, Python, Terraform, SF and Databricks. Note: • Interview process: 1 round - zoom, coding assessment may be required, candidates to be prepared to share screen. Pay Range: $50/hr - $55/hr The specific compensation for this position will be determined by a number of factors, including the scope, complexity and location of the role as well as the cost of labor in the market; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits including medical, dental, vision and 401K contributions as well as any other PTO, sick leave, and other benefits mandated by appliable state or localities where you reside or work.

Requirements

Must-haves

Hands-on experience with one or more AWS data lake technologies:
Data Lake: AWS Lake Formation, AWS Glue, AWS Step Function, AWS Lambda
Data Movement: AWS CLI, Python API, Spark, Python Boto3
Data Analytics: AWS Athena, S3 Select, EMR, Redshift
Compute/Storage: AWS S3, AWS EC2
Knowledge and experience with testing, releasing, and CI/CD pipeline deployments into AWS using:
Tools: Bitbucket/Git, Jenkins, Service Now
Log Trace: AWS CloudWatch, Splunk. Knowledge on Snowflake - Horizon Catalog and Databricks - Unity Catalog is a huge plus.
Minimum 6 years of experience of cloud data engineering
Glue, S3, Lambda, Step function, Lake Formation, Snowflake, Python, and Terraform, CI/CD
Conversant with AI Suite (Copilot/Claude/Agentic workflows)
Glue, S3, Lambda, Step function, Lake Formation, Snowflake, Python, Terraform, SF and Databricks.
Interview process: 1 round - zoom, coding assessment may be required, candidates to be prepared to share screen.

Nice-to-haves

Knowledge of at least one scheduling tool, Control-M Preferred
Working experience in one or more of the following languages: Python (Preferred),Java/Scala (Good to Have)
SF and Databricks

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

awspythonapijavaci/cdai

Platform: bullhorn
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto