Senior Data Platform Engineer

NextGen Federal Systems•Remote GA, GA

About The Position

This role serves as the senior technical owner of the enterprise data platform supporting Finance, Accounting, Sales, Customer Success, Product, HR and Executive Analytics. The Senior Data Platform Engineer is responsible for the architecture, engineering, administration, security, reliability, and continuous modernization of NextGen's cloud data platform. The role combines hands-on engineering with technical leadership, ensuring trusted, scalable, and well-governed data that supports operational reporting, financial close, executive decision making, AI initiatives, and enterprise analytics.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, Mathematics, Business, Finance, or related discipline.
8+ years of enterprise data engineering experience.
Expert experience with Snowflake, SQL, Informatica, Python, and modern cloud data platforms.
Experience designing enterprise data warehouses, dimensional models, and scalable ELT architectures.
Experience supporting financial reporting, reconciliations, and mission-critical production data platforms.
Experience administering cloud platforms including AWS services supporting enterprise data engineering.
Experience leading technical architecture, mentoring engineers, and influencing engineering standards.
Advanced SQL, Python, and data engineering practices.
Snowflake administration, security, optimization, and performance tuning.
Informatica Intelligent Data Management Cloud / PowerCenter or equivalent integration technologies.
AWS (S3, IAM, Secrets Manager) and cloud-native integration patterns.
Enterprise data modeling, governance, metadata, lineage, and data quality.
CI/CD, source control, monitoring, observability, automation, and DevOps practices.
Strong communication, collaboration, mentoring, and technical leadership skills.
Ability to influence architecture and engineering decisions across matrixed teams without direct authority.

Nice To Haves

Master's degree preferred or equivalent combination of education and experience.
Power BI administration and semantic modeling.
Financial systems and ERP data integration.
Experience with enterprise governance and AI-ready data platforms.
Experience leading modernization of enterprise data platforms.

Responsibilities

Own the enterprise Snowflake data platform including administration, security, RBAC, warehouse management, cost optimization, monitoring, performance tuning, and operational reliability.
Design, develop, and maintain scalable ELT/ETL pipelines using Informatica, SQL, Python and cloud-native services.
Define enterprise data architecture, integration standards, data modeling patterns, and engineering best practices.
Lead design and implementation of data ingestion, transformation, orchestration, and delivery supporting enterprise analytics.
Support critical Finance processes including month-end close, bookings, ARR, revenue, cost, reconciliations, and executive reporting.
Own production operations including monitoring, observability, incident response, root-cause analysis, disaster recovery planning, and platform resiliency.
Administer AWS services supporting the data platform including S3, IAM, Secrets Manager and related integrations.
Partner with Finance, Accounting, Product, Sales, Customer Success, HR, and IT to translate business requirements into scalable technical solutions.
Establish data quality, validation, reconciliation, lineage, metadata, and governance standards.
Develop automation for deployments, operational support, testing, monitoring, and platform administration.
Mentor engineers, perform architecture and code reviews, and provide technical leadership across the BI and Data Engineering organization.
Develop and maintain technical documentation, runbooks, operational procedures, and knowledge-transfer artifacts.
Evaluate emerging technologies and recommend improvements to scalability, security, performance, and operational excellence.
Perform other duties supporting enterprise data engineering objectives.