Data Engineer (USI8) (2400)

VSE AVIATION•Miramar, FL

1d•Hybrid

About The Position

We are seeking an experienced enterprise Data Engineer (6-10+ years) for the implementation, maintenance, and support of a next-generation cloud-based enterprise Data Lake / Data Lakehouse environment. The ideal candidate will have extensive cloud data platform experience with leading platforms like Snowflake and/or Microsoft Fabric, and deep knowledge and experience in data architecture and data engineering including: implementation of Medallion data architectures (Bronze/Silver/Gold), Analytics cubes, Star Schemas; construction of enterprise-oriented data models across business domains; establishment of high-performance on-prem, hybrid, and cloud data pipelines, and data integrations across key enterprise data repositories & systems using technologies such as Informatica and Azure Data Factory. This role will also be instrumental in establishing data engineering and governance standards, working closely with business stakeholders to standardize and normalize existing data domains, and ensuring data quality remains a core, go-forward asset.

Requirements

Bachelor’s degree in computer science, MIS, engineering, or related field Or an additional 3 years of specific work experience in lieu of degree.
6 years of significant experience in an enterprise Data engineering role
Strong professional proficiency in SQL
Proven Technical Experience with one or more: Snowflake, Microsoft Fabric, Databricks
Data Governance, Data Systems Architecture, and Data Modeling

Nice To Haves

Informatica, Azure Data Factory
MSFT SQL Server, Oracle
Microsoft Azure
Power BI
Golden Gate / Change Data Capture / Data Streaming
Aviation/Aerospace ERP
Structured, Semi-structured, and Unstructured Data Warehousing
Microsoft Purview
Azure DevOps or GitHub Actions
Kafka or Event Hubs
REST APIs and modern data integration techniques

Responsibilities

Design, implementation, and evolution of the organization's enterprise Data Lake/Lakehouse architecture.
Design and implement a scalable Medallion Architecture (Bronze, Silver, Gold) to support trusted, reusable data assets.
Develop robust ingestion frameworks for structured, semi-structured, and streaming data sources.
Build scalable ELT/ETL pipelines using cloud-native technologies and orchestration tools such as Informatica and Azure Data Factory.
Design dimensional models, curated data products, and semantic layers to support business intelligence and advanced analytics.
Implement data quality, lineage, cataloging, and metadata management best practices.
Optimize data storage, query performance, and workload management.
Establish CI/CD pipelines and Infrastructure-as-Code practices for data engineering solutions.
Collaborate with business stakeholders and application teams to understand data requirements and deliver scalable solutions.
Define and help enforce enterprise data engineering standards at with technical and business partners.
Partner with security and governance teams to implement role-based security, data privacy, and compliance controls.