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Metro mid-level data role at a well-known company with broad, popular skill requirements.
Transferable data engineering skills, but domain and GCP specialization moderately constrain cross-industry fit.
Explicit 4–6 years requirement plus mandatory GCP, BigQuery, dbt, and Spark skills.
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Design, build, and deliver scalable data products and analytics solutions on Google Cloud Platform (GCP) focused on Finance, Inventory Management, and Planning domains.
Develop and maintain high-performance end-to-end data pipelines and transformation frameworks using BigQuery, dbt, Python, SQL, and orchestrate workflows with Cloud Composer (Airflow).
Leverage Vertex AI to integrate advanced analytics and AI-driven capabilities; ensure data quality, governance, and produce clear technical documentation while collaborating across teams.
4-6 years of data engineering experience with building and scaling data-intensive applications.
Proficiency in SQL and Python; experience with open-source big data technologies (Spark, Flink, or Hive).
Experience with cloud platforms, preferably Google Cloud Platform (GCP).
Location: Bengaluru, India; Full-time role.
Experienced in designing and optimizing data models and pipelines for self-service analytics and enterprise-scale usage on GCP.
Skilled in leveraging AI/ML technologies such as Vertex AI to embed advanced analytics in data solutions.
Able to collaborate effectively with business stakeholders and cross-functional teams to align data strategies with business goals.