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# Cloud Data Developer/Engineer

- **Company:** Rang Technologies
- **Location:** Nutley, NJ, United States
- **Experience:** Expert
- **Salary:** $156,000.0 - $166,400.0
- **Contract:** Temporary to permanent
- **Skills:** Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Cloud Database, Cloud Engineering, Program Optimization, Computer Programming, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Data Systems, Dicom, Github, R (Programming Language), Python (Programming Language), Performance Tuning, Systems Development Life Cycle, Cloud Services, Tensorflow, SAS (Software), SQL Databases, System Testing, Tableau (Software), Unstructured Data, Cloud Platform System, Data Ingestion, Build Management, Pyspark, Kubernetes, Collibra, Data Analytics, Data Pipelines, GXP, Databricks
- **Published:** May 30, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e76daf4eb0d81e7c

## About the Role

Do you have experience in System development?, * 7-10+ years of experience in Data Engineering, Cloud Development, or related fields.

 * Strong expertise with AWS services including S3, Lambda, RDS, FSx/EFS, and cloud architecture best practices.
 * Advanced programming skills in Python, SQL, and PySpark with hands-on Databricks experience.
 * Experience building scalable data pipelines and working with structured, semi-structured, and unstructured data.
 * Experience with GitHub, Azure DevOps, Apache Airflow, CI/CD processes, and cloud-based data platforms., * Experience with life sciences data formats such as DICOM, FASTQ/BAM/PLINK, or SAS7BDAT.
 * Experience with Databricks administration, Unity Catalog, performance optimization, and data governance tools such as Immuta.
 * Familiarity with Tableau, SAS, R/Posit, machine learning frameworks, and Kubernetes/EKS.
 * AWS and/or Databricks certifications and knowledge of Computer System Validation (GxP/Non-GxP) environments.

## Description

The Cloud Data Developer/Engineer will design, develop, and optimize scalable cloud-based data platforms and pipelines supporting enterprise analytics and data-driven initiatives. The ideal candidate will have strong expertise in AWS, Databricks, Python, PySpark, and modern data engineering practices. This role requires hands-on experience with large-scale data processing, cloud-native architectures, and cross-functional collaboration to deliver secure, reliable, and high-performing data solutions., * Design and build scalable data pipelines for data ingestion, transformation, validation, and delivery using AWS, Python, and Databricks.

 * Develop and optimize cloud-native data solutions supporting structured, semi-structured, and unstructured datasets.
 * Collaborate with business and technical teams to architect technology solutions aligned with business requirements.
 * Implement CI/CD processes, orchestration workflows, and data platform best practices.
 * Support data governance, security, performance tuning, and platform optimization initiatives.
 * Manage projects through planning, design, development, testing, deployment, and production support phases.


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