Cloud Engineer

TalentOla; Austin (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

TalentOla in Austin is seeking an AWS Databricks Developer to join an Agile team building healthcare applications and implementing new features while following coding standards.

You will drive end-to-end data engineering initiatives, design cloud-native data architectures, and develop high-performance ETL/ELT pipelines using Spark/PySpark, AWS services, and CI/CD practices. Collaboration with stakeholders is essential.

Qualifications

• Experience with Databricks and Spark/PySpark in cloud data platforms.
• Strong AWS data services and DevOps practices experience.
• Healthcare data domain experience is a plus.
• Ability to collaborate with business and technical stakeholders to translate requirements into scalable data solutions.

Responsibilities

• Strong expertise in Databricks, Spark/PySpark, Teradata, AWS, and DevOps practices.
• Drive end-to-end data engineering initiatives in an Agile environment.
• Collaborate with stakeholders to translate requirements into scalable data solutions.
• Design, document, and implement cloud-native data architectures and engineering solutions.
• Develop high-performance ETL/ELT pipelines using Spark and PySpark for enterprise-scale data platforms.

Skills

Databricks

Spark/PySpark

Teradata

AWS

DevOps

Tools

Ab Initio

Shell Scripting

Unix/Linux

KSH

Git

Jenkins

Artifactory

CI/CD

Job description

What is in it for you?

As a AWS Databricks Developer you will be a part of an Agile team to build healthcare applications and implement new features while adhering to the best coding development standards.

Responsibilities

• Strong expertise in Databricks, Spark/PySpark, Teradata, AWS, and DevOps practices
• While driving end-to-end data engineering initiatives in an Agile environment.
• Key Responsibilities Collaborate with business and technical stakeholders to understand requirements and translate them into scalable data solutions.
• Design, document, and implement cloud-native data architectures and engineering solutions.
• Develop high-performance ETL/ELT pipelines using Spark and PySpark. Build and optimize data ingestion, transformation, and loading processes for enterprise-scale data platforms

Technical Skills

• Ab Initio Shell Scripting (Unix/Linux, KSH)
• AWS Cloud Services (S3, EC2, Lambda, Glue, SNS, SQS, ECS, IAM, CloudWatch) Data Warehouse & Data Lake Implementation CI/CD & DevOps Tools (Git, Jenkins, Artifactory)
• Production Support & Monitoring Agile Methodologies Preferred Skills Jira & Confluence.
• Healthcare Domain Experience Enterprise Scheduling Tools (CA7) Cloud Data Migration & Modernization Azure/AWS Integration.