Data Engineer with GCP

Position

Sr. Data Engineer with GCP

Must Have Skills

• Advanced GCP Data Engineering Expertise: Strong hands-on experience with GCP services such as BigQuery, Dataflow, Pub/Sub, Dataproc, and Cloud Storage for building large-scale data platforms.
• Data Architecture & Modeling: Deep understanding of data warehousing, dimensional modeling, and lakehouse architectures to support analytics and reporting.
• Leadership & Stakeholder Collaboration: Proven ability to lead engineering initiatives, mentor teams, and collaborate with business, analytics, and architecture stakeholders to deliver data solutions.
• Expertise in Scalable Data Pipeline Development: Expertise in designing and implementing high-performance ETL/ELT pipelines (batch and real-time) using Python, SQL, and frameworks like Apache Beam or Spark.

Nice to Have Skills

• Experience with Containerization & Kubernetes: Experience with Docker and Kubernetes (GKE) for deploying and managing scalable data platforms.
• Knowledge of Streaming & Real-Time Processing: Familiarity with Kafka, Pub/Sub streaming, and event-driven architectures for real-time data processing.
• Multi-Cloud Experience: Exposure to AWS or Azure environments for building and integrating cross-cloud data solutions.
• Machine Learning & Advanced Analytics Integration: Experience supporting ML pipelines (Vertex AI) or analytics workflows to enable data science and AI use cases.

Top 3 responsibilities

• Drive Customer Engagement Strategy Execution: Design and execute customer engagement plans, ensuring consistent communication, improved customer experience, and alignment with business objectives.
• Manage Customer Relationships & Satisfaction: Act as the primary point of contact for key customers, proactively address concerns, gather feedback, and ensure high levels of customer satisfaction and retention.