Senior GCP Architect

Hiring: Senior GCP Data Architect (L4 / L5)

Location: Kolkata – Face-to-Face Drive

Years of experience-9-19 yrs

Employment Type: Full-Time

We are seeking an experienced Senior GCP Data Architect to lead enterprise-scale cloud data architecture initiatives. This role demands strong technical depth in Google Cloud, distributed systems, and modern data platform patterns, along with the ability to guide teams and influence architectural decisions.

If you are passionate about building scalable, high-performance data ecosystems on Google Cloud, this opportunity is for you.

Primary Roles & Responsibilities

• Lead the design and implementation of end-to-end data architecture on Google Cloud Platform
• Select, evaluate, and integrate GCP-native and open-source data tools aligned with business objectives
• Architect and oversee scalable batch and streaming data pipelines (ETL/ELT)
• Translate complex business requirements into high-level and low-level solution designs
• Design and optimize modern data warehousing and real-time processing solutions
• Evaluate and recommend storage, compute, and streaming architectures
• Provide architectural governance, technical leadership, and mentorship
• Conduct design reviews and enforce best practices in cloud-native data engineering

Required Skills & Qualifications

• 9+ years (L4) / 13+ years (L5) of experience in Data Engineering / Data Architecture
• Strong expertise in data warehousing concepts and advanced data modeling
• Deep understanding of distributed systems and cloud-native architectures
• Hands-on expertise with GCP services:
• BigQuery
• Dataflow
• Dataproc
• Cloud Composer (Airflow)
• Pub/Sub
• Data Fusion
• Strong experience with Apache Spark (Batch & Streaming)
• Experience designing real-time and streaming data solutions
• Proficiency in SQL, Python, and Linux
• Experience with ETL/ELT frameworks like DBT or Apache NiFi
• Hands-on experience with messaging systems such as Kafka or Pub/Sub
• Strong understanding of Lambda & Kappa architectures and modern data platform patterns

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