Data Engineer - Data Warehouse Architect

ICF • Reston, VA

1d • Remote

About The Position

This position focuses on developing, implementing, and maintaining architecture solutions across a large enterprise data warehouse to support effective and efficient data management and enterprise-wide business intelligence analytics.

Requirements

• Minimum of 3 years of experience in data analysis.
• Strong analytical and problem-solving skills with attention to detail.
• Proficiency in SQL and ability to develop complex queries (e.g., multi-join), tune performance, and troubleshoot.
• Experience with Unix/Linux shell scripting for ETL automation.
• Familiarity with database tools and platforms (e.g., Teradata, Oracle, Non-Relational).
• Excellent verbal and written communication skills; ability to collaborate across all levels.
• Ability to prioritize and multi-task in a fast-paced environment.
• Knowledge of Java/J2EE, REST APIs, Web Services, and event-driven microservices.
• Experience with Kafka streaming, schema registry, OAuth authentication.
• Familiarity with Spring Framework, GCP services, Git, CI/CD pipelines, containerization, and data ingestion/data modeling.

Nice To Haves

• Experience with Databricks concepts and terminology (e.g., workspace, catalog).
• Proficiency in Python and Spark.
• Background in architecting real-time data ingestion solutions using microservices and Kafka.

Responsibilities

• Implement and optimize data pipeline architectures for sourcing, ingestion, transformation, and extraction processes, ensuring data integrity and compliance with organizational standards.
• Develop and maintain scalable database schemas, data models, and data warehouse structures; perform data mapping, schema evolution, and integration between source systems, staging areas, and data marts.
• Automate data extraction workflows and create comprehensive technical documentation for ETL/ELT procedures; collaborate with cross-functional teams to translate business requirements into technical specifications.
• Establish and enforce data governance standards, including data quality metrics, validation rules, and best practices for data warehouse design and architecture.
• Develop, test, and deploy ETL/ELT scripts using SQL, Python, Spark, or other relevant languages; optimize code for performance and scalability.
• Tune data warehouse systems for query performance and batch processing efficiency; apply indexing, partitioning, and caching strategies.
• Perform advanced data analysis, validation, and profiling using SQL and scripting languages; develop data models, dashboards, and reports in collaboration with stakeholders.
• Conduct testing and validation of ETL workflows to ensure data loads meet SLAs and quality standards; document testing protocols and remediation steps.
• Troubleshoot production issues, perform root cause analysis, and implement corrective actions; validate data accuracy and consistency across systems.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 11-50 employees