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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Warehouse Software Engineer III - **Company:** Babel - **Location:** Somerville, MA, United States - **Experience:** Experienced - **Salary:** $120,000.0 - $135,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Airflow, Big Data, BigQuery, Cloud Database, Cloud Storage, Continuous Integration, Directed Acyclic Graph (Directed Graphs), Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Loss, Data Manipulation Languages, Data Mining, Data Warehousing, DevOps, Identity and Access Management, Python (Programming Language), Performance Tuning, Software Engineering, Data Streaming, Systems Integration, Data Processing, Scripting, Google Cloud, Data Ingestion, Delivery Pipeline, Git, Google Cloud Functions, Google Bigquery, Software Version Control, Data Pipelines, Api Management - **Published:** August 15, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88044006/1 ## About the Role This is an experienced engineering role requiring strong Python skills, deep expertise across the entire GCP analytics stack, and hands-on experience managing and upgrading production Airflow environments., * U.S. Citizenship: Must be a U.S. Citizen due to federal government contract requirements. * Software Engineering Experience: 4-7+ years of professional software development experience, with at least 3+ years focused heavily on data warehousing, cloud data pipelines, and data platform operations. * Advanced Python Mastery: Production-grade Python development skills for data processing, custom pipeline tooling, and API integrations. * Airflow Platform Operations: Hands-on experience with Apache Airflow (Cloud Composer preferred), including DAG architecture, troubleshooting, environment configuration, and platform version upgrades. * GCP Ecosystem Expertise: Deep experience with the Google Cloud analytics suite-specifically BigQuery, Cloud Storage (GCS), Cloud Composer, Pub/Sub, and Cloud Functions/Run. * BigQuery Optimization: Advanced understanding of BigQuery architecture, DDL/DML, partitioning, clustering, slot allocation, and query cost-control strategies. * DevOps & Version Control: Proficient with Git, CI/CD pipelines, and modern software development workflows., * GCP Certification: Google Cloud Certified Professional Data Engineer (highly preferred). * High-Volume Data Experience: Experience working with multi-terabyte or billion-row datasets, unstructured web-scraped data, or streaming architectures. * Security & Compliance: Familiarity with government compliance frameworks, IAM policy design, and data encryption standards. ## Description In this role, you will be a key technical contributor responsible for architecting high-volume data ingestion pipelines into Google BigQuery, orchestrating complex workflow topologies in Apache Airflow (Cloud Composer), and maintaining the performance and reliability of our enterprise data warehouse. You will collaborate closely with cross-functional software, data, and analytics teams to integrate disparate commercial and government data sources into clean, highly available, and query-optimized data models., * Data Warehouse & Pipeline Engineering: Architect, build, and maintain production-grade ELT/ETL data pipelines that stream and batch high-volume, complex datasets into Google BigQuery. * Airflow Management & Platform Upgrades: Manage, monitor, and upgrade our Apache Airflow / Cloud Composer platform. Write clean, modular, and maintainable DAGs in Python, implement custom operators/hooks, and optimize cluster performance. * GCP Architecture & Optimization: Maintain and optimize core GCP data services (BigQuery, Cloud Storage, Cloud Functions/Run, Pub/Sub, IAM). Implement advanced BigQuery performance tuning (partitioning, clustering, slot management, and query cost control). * Python Engineering & Integrations: Develop high-performance Python scripts, API connectors, and automation tools for data extraction, schema validation, and third-party data integrations. * Data Quality & Integrity: Enforce strict data quality frameworks, monitoring, and automated alerting across all ingestion pipelines to ensure zero data loss and minimal latency. * Technical Leadership & CI/CD: Maintain infrastructure-as-code and CI/CD deployment pipelines for data workloads using Git. Assist in architectural reviews and mentor junior engineers on data warehousing best practices. ## Related Videos - [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) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Got AI ideas but no money? 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