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# Data Engineer

- **Company:** SSTech LLC
- **Location:** United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, JIRA, Big Data, Data Architecture, Data Cleansing, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, Python (Programming Language), Meta-Data Management, Performance Tuning, Data Streaming, Scripting, Core Data, Data Management, Data Pipelines, Databricks
- **Published:** September 9, 2026
- **Apply:** https://www.dice.com/job-detail/3056340d-c747-4df4-a77d-dfc550763076

## About the Role

* Proven experience as a Data Engineer or in a similar role, with previous experience in the pharmaceutical industry being highly regarded.
 * Hands-on experience with AWS, scripting and ETL pipelines
 * Strong proficiency in programming languages such as Python
 * Jira exp

Skills and Competencies

 * Strong analytical and problem-solving skills.
 * Excellent understanding of ETL/ELT processes and data pipeline development.
 * Knowledge of metadata management and data quality processes.
 * Proficiency in data modeling, data warehousing, and big data processing frameworks.
 * Excellent communication and collaboration skills.
 * Ability to learn new technologies quickly and develop new skills as needed.
 * Capable of identifying the best approach forward for various data engineering challenges.
 * Ability to work in a fast-paced, dynamic environment and manage multiple priorities.

## Description

The Data Engineer will be responsible for designing, developing, and maintaining data pipelines, ensuring, Data Pipeline Development

 * Design and develop ETL/ELT data pipelines
 * Ensure data pipelines are scalable, reliable, and efficient, meeting the needs of the organization.

Data Management

 * Implement and manage the data architecture, including Landing Zone, Bronze, Silver, and Gold layers within the Databricks environment.
 * Develop processes for data cleaning, normalization, and enrichment to maintain high data quality standards.

Data Governance

 * Integrate core data management with existing systems to ensure seamless data flow and consistency across platforms.
 * Develop a comprehensive tagging system for core data, ensuring that all data assets are tagged appropriately for easy retrieval and association.

Performance Optimization

 * Monitor and optimize the performance of data pipelines and processing workflows.
 * Ensure data architecture supports different stages of the data lifecycle, from development to production, with appropriate access controls.
 * Work closely with data scientists, data stewards, and other stakeholders to understand their data requirements and support their analytical needs.
 * Provide technical support and guidance to other team members and departments as needed.


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