Senior Data Engineer: Azure ETL & Data Warehousing

CACI International Inc; Arlington (VA); Presencial; USD 104.000 - 218.000; Jornada completa

Descripción de la vacante

CACI International Inc in Arlington, VA seeks a Senior Data Engineer to design, implement, and maintain robust data pipelines across the enterprise. The ideal candidate will have a DoD Secret clearance, a strong background in ETL, data warehousing, and Azure cloud services.

You will collaborate with data scientists and analysts to ensure data quality and timely delivery, document architectures, and optimize performance for large-scale datasets.

Formación

• 7+ years of related experience in data engineering.
• Strong experience with ETL processes using Azure services.
• 6+ years’ experience with coding languages (SQL, Python, R, SAS, JavaScript).
• 4+ years’ experience in ML, NLP, RPA, AI and related methods.
• Experience with complex SQL queries and data warehousing.

Responsabilidades

• Build, maintain, and optimize ETL data pipelines for loading data into the data warehouse.
• Integrate large, complex data sets to meet business requirements.
• Design scalable, reliable data warehousing solutions.
• Develop and maintain pipelines using Azure Data Factory and related Azure technologies.
• Collaborate with data scientists and analysts to deliver high-quality data solutions.
• Document data flows and system architecture.

Conocimientos

ETL pipelines

Azure data services

SQL

Python

Machine learning basics

AI/ML

Educación

BA/BS in Computer Science, Information Technology, Data Analytics, or related field

Herramientas

Azure Data Factory

Azure Databricks

Azure Data Lake Storage

Azure SQL Database

Azure Synapse Analytics

Descripción del empleo

CACI International Inc in Arlington, VA seeks a Senior Data Engineer to design, implement, and maintain robust data pipelines across the enterprise. The ideal candidate will have a DoD Secret clearance, a strong background in ETL, data warehousing, and Azure cloud services.

You will collaborate with data scientists and analysts to ensure data quality and timely delivery, document architectures, and optimize performance for large-scale datasets.