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Mid-level Data Engineer role, Bangalore location, generalist skillset, and cloud/Kubernetes requirements increase applicant competition.
Core data engineering skills transfer across industries, though industrial domain knowledge is a beneficial but not mandatory filter.
Explicit minimum experience plus mandatory Python/SQL, cloud, Kubernetes and customer-facing expectations increases filtering strictness.
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Lead design and implementation of scalable data engineering solutions using Cognite Data Fusion® platform.
Manage data integrations, extractions, modeling, and analysis with Cognite connectors, SQL, Python/Java, and Rest APIs.
Collaborate with data scientists, architects, and product teams to deliver and optimize industrial data solutions and support customer deployments.
Bachelor's or Master's in computer science or similar, or equivalent experience.
Minimum 4+ years in customer-facing, data-intensive roles.
Experience delivering production-grade data pipelines using Python, SQL, and Rest APIs.
Experience with distributed computing (e.g., Kubernetes) and managed cloud services (GCP and/or Azure).
Experienced in cross-functional environments collaborating with engineers, data scientists, and product managers to drive industrial digital solutions.
Strong operational and delivery focus with ability to manage end-to-end data pipeline implementations in production.
Familiarity with industrial data domains (oil & gas, manufacturing) and DevOps practices (Git, CI/CD).