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Northramp LLC

Data Engineer (BigQuery)

Washington, DC, United States
Reston, VA, United States
Bethesda, MD, United States

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Job details

Experience: 3 to 6 years of progressive, hands-on experience in data engineering with a focus on cloud data platforms and pipeline development.
Posting language: English
Posted: Nov 5, 2026

Original job description

Opportunity Overview Northramp is seeking a Data Engineer (BigQuery) to join the team supporting a mission-critical effort to consolidate, modernize, and operate our client's enterprise cloud services across IaaS, PaaS, and SaaS environments. You will design and operate cloud-native data pipelines, warehousing, and integration layers that make the client's data accessible, reliable, and analytics-ready. The role centers on modern cloud data platforms - with BigQuery as the primary analytical data warehouse - supporting the client's enterprise reporting, AI/ML, and program management data needs. This role is part of Northramp’s integrated delivery model, where engineers and advisors work as one team to bring sound judgment, disciplined execution, and deep federal experience to high-stakes modernization programs. Location & Work Arrangement Hybrid, based in the Washington, DC metro area. On-site presence at designated client locations is expected on a cadence aligned to program needs. Remote work is supported around mission and security requirements. This role is not open to candidates outside the DC, Maryland, and Virginia region. The Ideal Candidate You build data pipelines that run reliably in production - not just demos. You’ve designed schemas and ingestion pipelines against messy, real-world source systems, you understand data quality as an engineering discipline, and you can work comfortably within the access controls and compliance requirements of a federal environment.

Key Responsibilities

Design, build, and maintain scalable ELT/ETL data pipelines ingesting structured and semi-structured data from cloud services, APIs, databases, and file sources into BigQuery and other cloud data warehouses.
Develop and manage data models, schemas, and transformation logic using dbt (data build tool), SQL, and Python; enforce testing and documentation standards across the data layer.
Implement and operate pipeline orchestration using Apache Airflow (Cloud Composer), Prefect, or equivalent; monitor pipeline health, SLA adherence, and failure alerting.
Integrate data platforms with upstream source systems including cloud-native services (AWS RDS, Azure SQL, GCS/S3), operational databases, and third-party SaaS APIs.
Implement data access controls, column-level security, and encryption within BigQuery and related cloud storage services aligned to FedRAMP High and FISMA requirements.
Build and maintain data cataloging and lineage metadata practices to support data governance and auditability requirements.
Collaborate with Data Scientists and analysts to ensure data availability, schema stability, and performance of analytical workloads.
Develop and maintain infrastructure-as-code for data platform components using Terraform; participate in CI/CD pipeline integration for data assets.
Support data quality frameworks - profiling, anomaly detection, and SLA monitoring - across production data pipelines.
Contribute to ATO documentation and data security controls including data classification, retention policies, and audit logging.

Requirements

Required Qualifications

3 to 6 years of progressive, hands-on experience in data engineering with a focus on cloud data platforms and pipeline development.
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, or a related field. Relevant experience may substitute.
Strong SQL skills and hands-on experience with BigQuery as an analytical data warehouse; familiarity with BigQuery optimization (partitioning, clustering, materialized views).
Proficiency in Python for data engineering tasks.
Working knowledge of data services from at least one major cloud provider.
Understanding of data modeling principles and schema design for analytical workloads.
Familiarity with data governance concepts - cataloging, lineage, access controls, retention - and their application in regulated environments.
Knowledge of FedRAMP, FISMA, and NIST 800-53 data security requirements.
U.S. citizenship and the ability to obtain and maintain a DHS suitability / Public Trust clearance.
Eligible to work in the United States.

Desired Qualifications

Experience with dbt for data transformation and modeling in cloud warehouse environments.
Hands-on experience with pipeline orchestration tools such as Apache Airflow or Cloud Composer.
Google Cloud Professional Data Engineer certification.
AWS Certified Data Analytics Specialty or Azure Data Engineer Associate.
Security+ or equivalent certification.
Experience with streaming data platforms (Pub/Sub, Kafka, Kinesis).
DHS, or other federal data engineering experience.
Active Public Trust or higher clearance.

Clearance DHS suitability and a Public Trust background investigation are required for this role. Active Public Trust or higher clearance is preferred. Selected applicants will be subject to a security investigation and may need to meet eligibility requirements for access to controlled or classified information.

Benefits

Health Care Plan (Medical, Dental & Vision)
Retirement Plan (401k, IRA)
Life Insurance (Basic, Voluntary & AD&D)
Paid Time Off (Vacation, Sick & Public Holidays)
Family Leave (Maternity, Paternity)
Short Term & Long Term Disability
Training & Development
Work From Home
Wellness Resources
Employee Bonus Programs

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More about this job

Skills

BigQuery
Warehouse operations
Program management
Regulatory compliance
Data engineering
Create data models
dbt
SQL
Python
Documentation
Apache Airflow
AWS
Microsoft Azure
Operational databases
Cataloging
Infrastructure as code
IBM Terraform
CI/CD
Apply information security policies
Computer science
Data warehouse
Data modelling
Google Cloud
AWS certification
Data analysis
Security+
Apache Kafka

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