Data Engineer (UAP, EEB) at ECS Tech Inc

, West Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Mar, 26

Salary

165000.0

Posted On

23 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Pipeline Architecture, Database Schemas, ETL/ELT Procedures, Data Governance, SQL, Python, Spark, Unix/Linux Scripting, Java/J2EE, REST APIs, Microservices, Kafka, Spring Framework, GCP Services, CI/CD Pipeline, Data Modeling

Industry

IT Services and IT Consulting

Description

ECS is seeking a Data Engineer to work remotely. ECS is currently seeking a Data Engineer that develops, implements, and maintains architecture solutions across a large enterprise data warehouse to support effective and efficient data management and enterprise-wide business intelligence analytics. 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. Qualifications * 5-10+ years of experience * US Citizen or Green Card holder and must be able to obtain a Public Trust clearance. * 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 authentication. * Spring Framework and GCP Services in public cloud infrastructure, Git, CI/CD pipeline and containerization, data ingestion/data modeling * Develop Microservices using Java/J2EE Spring for ingesting large volume real-time events into Kafka topics. Architect solutions that make the data available to consumers in real time Salary Range: $140,000 - $165,000 General Description of Benefits [https://ecstech.com/careers/benefits]

Responsibilities

The Data Engineer will implement and optimize data pipeline architectures and develop scalable database schemas to support data management and business intelligence analytics. They will also automate data extraction workflows and establish data governance standards.