This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We are seeking a skilled GCP Data Engineer to join our Technology function within Software Engineering – BIBDA, based in Pune. In this role, the individual will design, build, and operationalise scalable data solutions on Google Cloud Platform, working closely with architects and cross‑functional teams. This opportunity is ideal for someone with strong experience in cloud data engineering, modern data modelling approaches, and a passion for continuous learning and knowledge sharing.
Job Responsibility:
Prepare Low Level Designs aligned with High Level Designs
Build, deploy, and operationalise robust data processing systems
Develop and optimise data pipelines using GCP services
Apply modern data pipeline patterns
Act as subject matter expert in GCP Data Engineering, supporting and mentoring junior team members
Apply learnings from new technologies to day-to-day delivery
Lead small teams or projects end-to-end
Contribute to organisational efficiency through process adoption, resource optimisation, tooling improvements
Actively contribute technical expertise to internal guilds and communities of practice
Requirements:
Strong SQL expertise
Proficient in GCP ecosystem (BigQuery, Dataflow, Dataproc, Looker)
Experienced with DBT (model development, Jinja templating, lineage generation)
Knowledgeable in Data Vault 2.0
6+ years overall experience, at least 2-4 years focused on GCP, DBT, and Data Vault 2.0
B.E./B.Tech/BCA/MCA/BSc/MSc in Computer Science or related field
Google Cloud Certified Professional Data Engineer certification is advantageous
Collaborative, adaptable, committed to quality, timely delivery, policy adherence
What we offer:
Exposure to large-scale enterprise-grade data platforms
Opportunities to work on modern cloud data engineering solutions
Collaborative environment valuing learning and continuous improvement
Chance to influence data engineering practices and contribute to technical communities