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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - GCP - **Company:** Megazone Cloud US - **Location:** Rochester, NY, United States - **Experience:** Expert - **Salary:** $145,000.0 - $165,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, BigQuery, Cloud Computing, Cloud Storage, Software Quality, Code Review, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Dataspaces, Data Flow Control, Github, Identity and Access Management, Python (Programming Language), Metadata, Power BI, Tensorflow, SQL Databases, Data Streaming, Data Logging, Data Processing, Business Intelligence Development Studio, Google Cloud, Cloud Monitoring, Snowflake, Change Data Capture, Git Flow, Google Cloud Functions, Data Management, Machine Learning Operations, Terraform, Looker Analytics, Databricks - **Published:** August 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=5f84280e7ee9940e ## About the Role Megazone Cloud is looking for a Senior Data Engineer to help lead and define our data-driven culture on Google Cloud. You are a "builder" at heart, a seasoned expert who thrives on solving complex problems. You have a startup mentality, a thirst for knowledge, and the ability to lead projects and mentor others. You have deep expertise in data architecture and data wrangling, and you are a master of Python, SQL, and BigQuery. You've architected platforms that other people's businesses run on, and you know the difference between a pipeline that works and a pipeline that survives contact with the real world. At L5 you lead ambiguous projects from conception to delivery and act as the technical point of contact for a client workstream. You're a "force multiplier" - your presence makes the engineers around you better., * 5-8+ years of professional data engineering experience. * Deep, expert-level proficiency with Python. * Deep, expert-level proficiency with SQL. * Hands-on, expert-level experience with BigQuery and the wider Google Cloud data stack. * Hands-on experience with a SQL transformation framework - Dataform or dbt. * Deep expertise in designing and architecting scalable data platforms, including batch and streaming ingestion patterns. * Strong infrastructure-as-code practice - Terraform (or equivalent) and CI/CD. * Proven ability to lead complex, ambiguous projects from conception to delivery. * Experience mentoring other engineers and helping to level up the team. * Exceptional communication skills, the flexibility to think fast, and the credibility to present a decision to technical and non-technical audiences alike. * A "builder" mindset, a startup mentality, and a genuine thirst for knowledge., * Experience with GenAI, AI/ML frameworks, and MLOps - including data modeling and metadata that gets a client ready for agentic workloads. * Looker / LookML, Power BI, or other BI tooling on top of a cloud warehouse. * Change-data-capture and real-time streaming at production scale. * Data governance and catalog work - glossary, policy tags, lineage, data contracts. * Cross-platform depth - AWS, Databricks, or Snowflake. We meet clients where they are. * Certifications in GCP, Databricks, Snowflake, or AWS. ## Description * Architect, build, and lead: Architect and own scalable, high-performance data platforms and pipelines on Google Cloud - not just maintain them. * Define the data ecosystem: Drive the strategy for a client's data environment, leveraging BigQuery and the GCP data stack to create powerful, efficient data models. * Write and review critical code: Develop clean, optimized, and automated solutions using Python and SQL. Set the standard for code quality and run rigorous, kind code reviews. * Face the client: Lead technical discussions in your workstream - demos, working sessions, architecture reviews, and knowledge-transfer workshops - and translate business requirements into technical decisions. * De-risk: Prototype solutions, evaluate new services, and surface risks before they become escalations. * Collaborate and multiply: Act as a key "force multiplier" within our cross-functional US and offshore teams, and mentor junior engineers into engineers you'd want on your next project. * Be a flexible leader: Embrace a "builder" mentality. In a startup, you'll have the flexibility to solve diverse challenges, and your voice will be critical in shaping our technical roadmap. The Stack We Build On Layer What we build with Warehouse & compute BigQuery - partitioning, clustering, authorized views, BI Engine, BigQuery ML Ingestion & streaming Datastream, Pub/Sub, Dataflow, Cloud Functions / Cloud Run, Cloud Storage Transformation Dataform or dbt - SQL models, assertions/tests, Git-based workflows Orchestration Cloud Composer (Airflow), Cloud Workflows, Eventarc Governance & catalog Dataplex / Knowledge Catalog - glossary, policy tags, lineage, column-level security Observability Cloud Monitoring + Logging - SLIs/SLOs, alerting, data quality metrics IaC & CI/CD Terraform, GitHub Actions, Secret Manager, least-privilege IAM Analytics & AI Looker, Power BI, Vertex AI, Gemini ## 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) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Why Git Still Matters](https://www.wearedevelopers.com/videos/100288-why-git-still-matters) - [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) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [Got AI ideas but no money? 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