Data Engineer

Everforth ECS is seeking a Data Engineer to work remotely . Please Note: This position is contingent upon additional funding.

Everforth ECS is seeking a Data Engineer to work on our US Postal Service Data Analytics team. This is an exciting position that develops, implements, and maintains data workflow and architecture solutions across large enterprise warehouses and pipelines. These solutions will be used to support effective and efficient data management and enterprise-wide business intelligence and efficiency analytics for the US Postal Service.



Responsibilities:

• Implement, and optimize data pipeline architectures for data sourcing, ingestion, transformation, and extraction processes, ensuring data integrity, consistency, 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 develop comprehensive technical documentation for ETL/ELT procedures; collaborate with cross-functional teams to translate business requirements into technical specifications and data schemas.
• Establish and enforce data governance standards, including data quality metrics, validation rules, and best practices for data warehouse design, architecture, and tooling.
• Develop, test, and deploy ETL/ELT scripts and programs using SQL, Python, Spark, or other relevant languages; optimize code for performance, scalability, and resource utilization.
• Implement and tune data warehouse systems, focusing on query performance, batch processing efficiency, and resource management; utilize 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 scheduled SLAs and business quality standards; document testing protocols, results, and remediation steps.
• Perform root cause analysis for data processing failures, troubleshoot production issues, and implement corrective actions; validate data accuracy and consistency across systems; support iterative development and continuous improvement of data pipelines.

Salary Range: $130,000-$145,000

General Description of Benefits