Who Are We?
Groundswell is a premier technology integrator and solution provider, resolutely committed to solving the most complex challenges facing federal agencies today. Our name, Groundswell, represents our commitment to be an unstoppable, seismic change in government. Ours is a small company culture with big company reach and results. Are you ready to be audacious, be bold and drive change at a rapid pace? Join us, where we’ll make a greater impact together.
What You'll do:
Groundswell is seeking an experienced Data Engineer to build secure, reliable data capabilities for a mission-focused platform that connects authoritative sources, operational data, and analytical services. This role spans data ingestion, integration, quality, governance, and pipeline operations. You will help make complex data usable and trustworthy by designing repeatable workflows that preserve provenance, enforce access controls, and support decision-ready applications and AI-enabled capabilities in controlled environments.
What You'll Do
Design, develop, and operate batch and streaming ETL/ELT pipelines that ingest data from multiple structured and semi-structured sources into secure cloud data platforms.
Onboard new data sources by defining schemas, mappings, interfaces, validation rules, ownership, and operational support procedures.
Build automated data-quality checks for completeness, accuracy, consistency, timeliness, and referential integrity, with actionable monitoring and alerting.
Create data transformations and processing workflows that support operational applications, analytics, machine learning, and retrieval or inference workflows.
Preserve data lineage, provenance, version history, audit trails, and handling metadata throughout the data lifecycle so users can understand where data came from and how it was changed.
Implement secure data practices, including least-privilege access, encryption, secrets management, privacy protections, and controls appropriate for sensitive or classified information.
Develop and maintain data models, curated datasets, and service interfaces that provide consistent, well-documented access to authoritative information.
Automate deployments and pipeline operations using Infrastructure as Code, CI/CD, workflow orchestration, and environment-specific configuration.
Optimize data pipelines for scalability, resiliency, performance, and cost across cloud platforms, including effective partitioning, parallelism, storage, and compute utilization .
Troubleshoot failures across distributed data systems using logs, metrics, lineage, and operational signals; communicate root causes and recovery plans clearly.
Collaborate with software engineers, cloud engineers, data scientists, security teams, architects, and customer stakeholders to translate mission needs into measurable data products.
Produce maintainable data contracts, architecture documentation, runbooks, test plans, and operational guidance for the broader team.
Contribute technical expertise to solution planning and proposal efforts involving secure data platforms and AI-enabled mission capabilities.
Required Qualifications
Bachelor’s degree in Computer Science , Computer Engineering, Mathematics, Statistics, or a related technical field.
5+ years of professional data engineering experience, including production pipeline development and operations.
Strong SQL expertise , including query optimization, data modeling, joins, window functions, and analysis of large datasets.
Proficiency in Python, Java, R, or other programming language used for data engineering.
Experience with modern data-integration and workflow frameworks such as Apache Airflow, AWS Glue, Spark, or comparable tools.
Experience with Jupyter Notebook or other equvialent tools for analyzing data.
Experience with Python libraries such as numpy , panda, and other libraries like this.
Hands-on experience with at least one major cloud provider, with AWS experience…