About the Role
Are you passionate about building robust data architectures that power enterprise-scale analytics?
We are seeking a high-performing Senior Data Engineer / Analyst to take ownership of our scalable data pipelines and drive enterprise analytics initiatives. In this role, you won't just be moving data; you will be architecting solutions on Google Cloud Platform (GCP), optimizing performance at scale, and delivering the foundational data assets that drive our strategic decision-making. If you thrive in a fast-paced environment and love turning raw data into high-quality, actionable insights, we want you on our team.
What You Will Do (Key Responsibilities)
Architect & Scale: Design, build, and deploy robust, end-to-end data ingestion pipelines from diverse, complex sources into our modern data stack.
Empower Analytics: Engineer and model highly optimized analytical data marts, joining complex processed data assets to empower data scientists and business analysts.
Optimize & Innovate: Drive system performance and cost-efficiency. You will expertly optimize queries and manage storage costs leveraging BigQuery partitioning, clustering, and materialized views.
Champion Data Quality & Governance: Take the lead on data integrity. Implement and manage rigorous data cleaning, annotation, and access control policies in strict alignment with enterprise governance standards.
Ensure Reliability: Proactively monitor pipeline health and data freshness. You will lead root-cause analysis and swift resolution for any data quality or pipeline bottlenecks, ensuring zero downtime for critical metrics.
What You Bring (Qualifications & Skills)
Core Technical Stack:
Programming & Scripting: Advanced proficiency in SQL and Python for complex data manipulation and pipeline automation.
Cloud Infrastructure: Deep, hands-on experience with GCP (Google Cloud Platform), specifically BigQuery.
Data Tooling: Strong experience with modern cloud-native data transformation and orchestration tools (e.g., dbt, Plx, or similar ecosystem tools).
Experience & Mindset:
4 to 7 years of dedicated experience in Data Engineering, BI, or Data Architecture.
Proven track record of building and optimizing ETL/ELT pipelines at scale.
A strong analytical mindset with a relentless focus on performance tuning and cost optimization.
Excellent problem-solving skills and the ability to work autonomously to debug complex data issues.
Why Join Us?
Future-Ready AI Transformation: Play a pivotal role in a large-scale, "AI-first" enterprise transformation. You will get hands-on experience building the data foundations for tomorrow, working directly with futuristic AI tools and next-generation architecture.
Impactful Work: Your pipelines will directly feed the advanced analytics and AI models that shape our overall enterprise strategy.
Modern Tech Stack: Work with the latest cloud-native technologies in a forward-thinking, engineering-led data culture.
