Senior Data Engineer - Cloud ETL & Pipelines

Groundswell Corporation; McLean (VA); On-site; USD 90,000 - 175,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

401K match with immediate vesting

Paid time off

Tuition reimbursement and professional

Flexible work schedule

On-site gym and childcare option

Job summary

Groundswell Corporation seeks a senior data engineer to design, build, and operate scalable ETL/ELT pipelines across secure cloud data platforms. You will collaborate with federal customers and cross-functional teams to deliver reliable data products.

The role emphasizes data quality, security, governance, and efficient pipeline operations, with expertise in SQL, Python, Airflow, and cloud services to support analytics, ML, and operational use cases.

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 equivalent tools for analyzing data.
• Experience with Python libraries such as numpy, pandas, and other libraries like this.
• Hands-on experience with at least one major cloud provider, with AWS experience strongly preferred.
• Experience implementing data-quality frameworks, validation processes, monitoring, and alerting for production pipelines.
• Working knowledge of data security, access controls, encryption, auditability, and governance in a regulated, restricted, or compliance-oriented environment.
• Experience working with APIs and structured data formats such as JSON, XML, CSV, and Parquet.
• Ability to document technical decisions and collaborate with multidisciplinary teams and customer stakeholders.
• Must be a U.S. Citizen per contract requirements.
• Must be able to obtain and maintain a Public Trust Clearance in accordance with contract requirements.
• Active Public Trust Clearance.
• Preference given to candidates local to the Washington, DC metro area.
• Certifications: AWS Data Engineer Certification, Databricks, cloud data engineering, or other relevant professional certification is preferred.

Responsibilities

• 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.

Skills

SQL

Python

Java

R

Airflow

AWS

Data modeling

Data security

APIs/JSON/Parquet

Pandas/Numpy

Cloud data platforms

Education

Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field

Tools

Apache Airflow

AWS Glue

Spark

Jupyter Notebook

Job description

Groundswell Corporation seeks a senior data engineer to design, build, and operate scalable ETL/ELT pipelines across secure cloud data platforms. You will collaborate with federal customers and cross-functional teams to deliver reliable data products.

The role emphasizes data quality, security, governance, and efficient pipeline operations, with expertise in SQL, Python, Airflow, and cloud services to support analytics, ML, and operational use cases.