Senior Analyst - Data Engineering

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. Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.