Azure Data Engineer

Lorven Technologies Inc

Texas City, TX, United States

15 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

6 years minimum

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Microsoft Windows Big Data Cloud Computing Cloud Database Information Engineering Data Integration Extract Transform Load (ETL) Data Transformation Distributed Data Store Python (Programming Language) Data Processing Scripting

+7 more

Enterprise Software Applications Azure Data Factory Pyspark Information Technology Software Version Control Data Pipelines Databricks

Job description

Provide onsite desktop and field services support for hardware, Windows OS, applications, and endpoint-related incidents.
Administer endpoint management tools to deploy software packages, patches, configurations, and security policies.
Perform desktop and endpoint patching, monitor compliance, and remediate failed or missing patches.
Support desktop imaging, configuration baselines, workstation standardization, and endpoint security.
Troubleshoot escalated incidents, perform root cause analysis, and implement long-term solutions.
Monitor endpoint health and collaborate with Service Desk, Network, Application, Security, and Infrastructure teams.
Maintain technical documentation and support asset/inventory management activities.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field, or equivalent practical experience in data engineering and cloud technologies.
3 6 years of experience in Data Engineering, Azure Data Engineering, ETL/ELT development, or related roles.
Strong hands-on experience with Azure Data Factory (ADF) for developing, orchestrating, scheduling, and monitoring data pipelines.
Strong experience with Azure Databricks for data processing, transformation, and analytics workloads.
Hands-on experience with PySpark for large-scale data processing and distributed data transformations.
Strong proficiency in Python for data engineering, scripting, and automation.
Experience with Git and version control practices for collaborative development and code management.
Experience designing and developing scalable data pipelines and implementing data transformation processes.
Strong understanding of data integration, ETL/ELT concepts, data processing, and cloud-based data engineering practices.
Excellent problem-solving skills with strong attention to detail and the ability to troubleshoot data pipeline and processing issues.
Strong communication and collaboration skills with the ability to work effectively with technical and cross-functional teams.