> Markdown version of [/jobs/ext/4607978-data-engineer-bigquery](https://www.wearedevelopers.com/jobs/ext/4607978-data-engineer-bigquery). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer (BigQuery) - **Company:** Northramp LLC - **Location:** Washington, DC, United States (Remote available) - **Experience:** Experienced - **Salary:** $135,000.0 - $165,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Audit Trail, BigQuery, Software as a Service, Cloud Computing, Cloud Database, Cloud Storage, Cluster Analysis, Software Documentation, Information Systems, Databases, Continuous Integration, Data as a Services, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Security, Data Warehousing, Database Queries, Digital Assets, Infrastructure as a Service (IaaS), Python (Programming Language), SQL Azure, Operational Databases, Platform as a Service (PAAS), Cloud Services, SQL Databases, Data Streaming, Google Cloud, Data Classification, Data Ingestion, Azure Data Factory, System Availability, Data Build Tool (dbt), Data Layers, Amazon Relational Database Service, Semi-structured Data, Information Technology, Data Analytics, Apache Kafka, Data Management, Terraform, Data Pipelines, Serverless Computing - **Published:** November 6, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-engineer-bigquery-washington-dc--c08b52ea-dc23-4a54-ada6-e837e46108ac ## About the Role Infrastructure as a Service (IaaS), Software as a Service (SaaS), Cloud Computing, Platform as a Service (PaaS), Analysis Skills, Data Management, Data Warehousing, Project/Program Management, Artificial Intelligence (AI), Customer Support/Service, 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., * 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. ## Description * 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.