Join a leading Technology & Transformation practice to unlock the potential of vast data landscapes. We empower companies to manage data from diverse sources, transforming it into actionable insights for informed decision-making and a competitive edge. Our expertise spans business intelligence, data management, performance management, and cutting-edge analytics including big data, cloud, cognitive, and machine learning.

This role focuses on delivering impactful data engineering solutions within the Google Cloud Platform (GCP) ecosystem.

Lead the architecture and delivery of scalable data engineering solutions on Google Cloud Platform. Define and enforce cloud-based data platform engineering standards. Drive the implementation of enterprise-grade data pipelines using BigQuery, Dataproc, Cloud Composer, Python, and Spark. Oversee the development, optimization, and governance of robust data processing frameworks. Collaborate with business stakeholders to shape data strategies and transformation roadmaps. Manage end-to-end project lifecycles, including resource planning, risk mitigation, and effective stakeholder communication. Champion performance optimization, cloud cost efficiency, and operational excellence. Lead and mentor engineering teams, cultivating a culture of innovation and continuous learning. Ensure strict adherence to data governance, security, and compliance mandates.

A seasoned professional with 7 to 10 years of extensive experience in leading data engineering initiatives, specifically on Google Cloud Platform (GCP). Demonstrate deep expertise in BigQuery, Cloud Composer, and Dataproc. Possess advanced proficiency in Python, SQL, and PL/SQL. Show strong, hands-on experience with Spark/PySpark for large-scale data processing. Proven track record in architecting and delivering enterprise data platforms. Exhibit a solid understanding of cloud architecture principles, security, governance, and operational best practices. Experience in managing technical teams and overseeing complex project deliveries is essential. Excellent stakeholder management, communication, and leadership skills are critical for success. Familiarity with Dataflow, Pub/Sub, Looker, or Vertex AI is a plus. Knowledge of modern Data Lake and Lakehouse architectures is beneficial. Exposure to DevOps, DataOps, and CI/CD frameworks is advantageous. Experience with cloud migration and modernization programs is desirable. Understanding of AI/ML data engineering ecosystems is a plus. Experience in solution estimation, proposal development, and client engagement activities is valued.