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Specialized GCP/Kafka/dbt skillset and non-Tier1 brand yield moderate competition in Pune.
Platform engineering skills transfer across industries but require specific cloud/tooling, so medium sensitivity.
Multiple mandatory cloud, data platform, and programming skills create high shortlisting strictness.
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Build and maintain batch and real-time data pipelines using Dataflow and Kafka to support the Operational Data Store.
Develop and monitor Airflow (Cloud Composer) DAGs to ensure timely data delivery and orchestrate workflows.
Deploy and manage cloud infrastructure on GCP using Terraform; develop internal APIs and microservices with FastAPI and Golang to enhance platform capabilities.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Software Engineering, or related technical field with strong foundation in Distributed Systems, DBMS, Algorithm Design, and Real-time Computing.
Proficiency in Python (advanced), Golang (intermediate), and SQL.
Experience working with GCP components including Cloud Run, BigQuery, Cloud SQL, Cloud Spanner, Cloud Storage, Managed Airflow (Cloud Composer), Pub/Sub, Eventarc, Artifact Registry, and Secret Manager.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building scalable data pipelines and event-driven architectures using Google Cloud Platform services.
Capable of managing complex data infrastructure including orchestration (Airflow), containerization (Docker), and CI/CD pipelines (GitLab/Jenkins).
Familiarity with software development of internal APIs/microservices and data modeling (using dbt) with strong operational and automation focus.