Remote Data Engineer

1w1 week ago

ECS

US · Full-time · $130,000 – $145,000

About this role

Everforth ECS is seeking a Remote Data Engineer to work on the US Postal Service Data Analytics team. This position develops, implements, and maintains data workflow and architecture solutions across large enterprise warehouses and pipelines. These solutions support effective data management and enterprise-wide business intelligence for the US Postal Service.

The role involves implementing and optimizing data pipeline architectures for sourcing, ingestion, transformation, and extraction processes. Engineers ensure data integrity, consistency, and compliance with organizational standards while developing scalable database schemas and data models. They perform data mapping and integration between source systems, staging areas, and data marts.

Collaboration with cross-functional teams translates business requirements into technical specifications and data schemas. The position establishes data governance standards, including quality metrics and validation rules for warehouse design. Work occurs in a fast-paced environment supporting US Postal Service efficiency analytics.

Data Engineers automate extraction workflows, develop ETL/ELT documentation, and conduct advanced analysis using SQL and scripting. They test workflows to meet SLAs, perform root cause analysis for failures, and drive continuous improvement of pipelines. Note: This position is contingent upon additional funding.

Requirements

Must be a US Citizen or Green Card holder, and must be able to obtain a Public Trust Clearance
5-10+ years of experience building and designing data extraction, formatting and engineering tools, workflows, pipelines and ETL / ELT processes
Detail oriented with strong analytical and problem-solving skills
Ability to use database tools, techniques, and applications (e.g., Teradata, Oracle, Non-Relational) to develop complex SQL statements (e.g., multi-join), and to tune and troubleshoot queries for optimal performance
Skill using Unix/Linux shell scripting to develop and implement automation scripts for Extract, Transfer Load (ETL) processes
Communications skills (both verbal & written) - ability to work and communicate with all levels in team structure
Team player with the ability to prioritize and multi-task, work in a fast-paced environment, and effectively manage time
Java/J2EE and REST APIs, Web Services and building event-driven Micro Services and Kafka streaming using Schema registry, OAuth

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; perform root cause analysis for data processing failures