GCP Spanner Data Engineer

Prodapt is the largest specialized player in the Connectedness industry. As an AI-first strategic technology partner, Prodapt provides consulting, business reengineering, and managed services for the largest telecom and tech enterprises building networks and digital experiences of tomorrow. A ServiceNow-invested company, Prodapt has been recognized by Gartner as a Large, Telecom-Native, Regional IT Service Provider. A “Great Place To Work® Certified™” company, Prodapt employs over 6,000 technology and domain experts across the Americas, Europe, India, Africa, & Japan. Prodapt is part of the 130-year-old business conglomerate The Jhaver Group, which employs over 32,000 people across 80+ locations globally.

Looking for a seasoned GCP Data Engineer to design, build, and maintain large-scale data pipelines and infrastructure on Google Cloud Platform. You will work closely with data architects, analysts, and product teams to deliver reliable, performant, and cost-efficient data solutions.

Responsibilities

Design and implement scalable data pipelines using GCP-native services (Dataflow, Dataproc, Pub/Sub, Cloud Composer/Airflow)

Architect and optimize BigQuery datasets, tables, and queries for analytical workloads at scale

Design and manage Cloud Spanner schemas for globally distributed, strongly consistent transactional data

Build and maintain data models, transformations, and orchestration workflows using Cloud Workflows and related tools

Develop backend data services and ETL/ELT scripts in Python

Integrate and manage Firestore for real-time, document-oriented data use cases

Design and manage the GraphQL schema

Build highly optimized resolver functions that bridge the GraphQL schema directly to data warehouses

Implement GraphQL Subscriptions to stream live data, event changes, or real-time metrics using message brokers like Apache Kafka

Implement data governance, lineage, and quality frameworks using tools like Dataplex or Data Catalog

Collaborate on infrastructure-as-code using Terraform for GCP resource provisioning

Monitor pipeline health, optimize costs, and troubleshoot production issues

Mentor junior engineers and contribute to architectural decisions and best practices

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related field; OR equivalent combination of education and relevant experience.

10+ years of overall experience in data engineering or a related field

5+ years of hands-on experience on Google Cloud Platform

Strong proficiency in Python for data processing, automation, and pipeline development

Deep expertise in BigQuery — schema design, partitioning, clustering, query optimization, cost governance

Production experience with Cloud Spanner — schema design, interleaving, transaction patterns, and performance tuning

Solid understanding of GCP data services: Dataflow, Pub/Sub, Cloud Storage, Dataproc, Cloud Composer

Experience with Cloud Workflows for serverless orchestration

Hands-on experience with Firestore (Native mode preferred) for NoSQL/document storage patterns

Strong SQL skills and understanding of data warehousing concepts

Experience with CI/CD pipelines (Cloud Build, GitHub Actions) and version control (Git)

Preferred / Nice To Have

Experience with dbt for transformation layer on BigQuery

Familiarity with streaming architectures (exactly-once semantics, late data handling)

Knowledge of data mesh or data lakehouse patterns

Exposure to Vertex AI or ML pipelines for MLOps workflows

GCP Professional Data Engineer certification