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# Data Engineer

- **Company:** Global Services, LLC
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Contract
- **Skills:** Adaptable Database Systems, Application Programming Interfaces (APIs), Microsoft Azure, Cloud Computing, Cloud Computing Security, Cloud Database, Code Review, Continuous Integration, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Database Queries, Python (Programming Language), Query Optimization, Azure Data Lake, SQL Stored Procedures, SQL Databases, Systems Integration, Data Logging, Azure Data Factory, Snowflake, Apache Spark, Git, Data Lakes, Pyspark, Semi-structured Data, Information Technology, Restful APIs, Software Version Control, Data Pipelines, Databricks
- **Published:** October 18, 2026
- **Apply:** https://www.dice.com/job-detail/a0640717-2102-4bb2-a842-fdd6d2db5fb1

## About the Role

· We are seeking a Data Engineer with 3-5 years of experience to design, build, and support scalable data pipelines and cloud-based analytics solutions. The role requires hands-on expertise in ETL/ELT, Snowflake, Azure Data Factory, and Azure Databricks, with a strong focus on data quality, performance, reliability, and secure delivery., · Bachelor degree in Computer Science, Information Technology, Engineering, or a related field.

· 3-5 years of hands-on experience in data engineering, data integration, or cloud data-platform development.

· Strong experience designing ETL/ELT pipelines and working with dimensional/data-warehouse concepts.

· Hands-on proficiency with Snowflake, including data loading, transformations, query tuning, and warehouse optimization.

· Practical experience with Azure Data Factory for linked services, datasets, pipelines, triggers, and orchestration.

· Practical experience with Azure Databricks, Apache Spark/PySpark, notebooks, clusters, and Delta Lake concepts.

· Strong SQL skills and working proficiency in Python; experience integrating relational, file, API, and cloud-storage sources.

· Understanding of Git-based version control, CI/CD, Agile delivery, and secure cloud data practices.

· Strong analytical, troubleshooting, communication, and documentation skills.

PREFERRED SKILLS

· Azure Data Lake Storage Gen2, Delta Lake, Azure DevOps, Git, REST APIs, data governance/lineage, Snowpipe, dbt, and Microsoft Azure or Snowflake certifications.

## Description

· Design, develop, test, deploy, and maintain batch and near-real-time ETL/ELT pipelines for structured and semi-structured data.

· Build and orchestrate ingestion and transformation workflows using Azure Data Factory and Azure Databricks.

· Develop scalable data models, transformations, stored procedures, and performance-optimized workloads in Snowflake.

· Use PySpark, Python, and SQL to cleanse, integrate, validate, and transform data across cloud and enterprise sources.

· Implement monitoring, logging, alerting, retry, and error-handling mechanisms to improve pipeline reliability.

· Apply data-quality checks, reconciliation controls, lineage, documentation, security, and access-control standards.

· Collaborate with architects, analysts, application teams, and business stakeholders to translate requirements into data solutions.

· Participate in code reviews, CI/CD deployments, production support, root-cause analysis, and continuous optimization.