Full Job Description
Senior Data Engineer - GCP
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.
What You'll Do
• 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
MegazoneCloud • Senior Data Engineer (L5) • 2
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
What You Bring
• 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.
Bonus Points (Nice-to-Haves)
• 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.