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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer (BigQuery / Cloud Data Platforms) - **Company:** Northramp LLC - **Location:** Washington, DC, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), 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 Vault Modeling, Database Queries, Digital Assets, Dimensional Modeling, Python (Programming Language), SQL Azure, Operational Databases, 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:** May 23, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=f170780b4dd17759 ## About the Role Do you have experience in Security compliance frameworks implementation?, Do you have a Bachelor's degree?, 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 (ingestion, transformation, pipeline scripting). * Experience with dbt for data transformation and modeling in cloud warehouse environments. * Hands-on experience with pipeline orchestration tools: Apache Airflow, Cloud Composer, or equivalent. * Working knowledge of cloud storage and data services across at least one major cloud provider (GCS, S3, Azure Blob Storage, Cloud Spanner, Redshift, or equivalent). * Understanding of data modeling principles (dimensional modeling, data vault, or similar) 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. Desired Qualifications * Google Cloud Professional Data Engineer certification. * AWS Certified Data Analytics Specialty or Azure Data Engineer Associate. * dbt certification. * 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Hacking MSSQL on Cloud. 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