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Mid-level data engineer role, Pune metro and generalist cloud/databricks skillset increase candidate competition.
Core data engineering skills are transferable across industries, though enterprise source experience adds some domain bias.
Explicit minimum experience, specific Databricks/multi-cloud/ETL/Scala/Python/infra tooling make filters strict.
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Develop and maintain data products based on KONE's Data Foundation to enable scalable analytics, AI, and digital use cases across the organization.
Responsible for designing, optimizing, and troubleshooting data pipelines using a multi-cloud technology stack including AWS, Azure, Databricks, and related tools.
Ensure reusability and quality of data assets in a multi-hop medallion architecture (bronze, silver, gold layers) and publish data products in Unity Catalog.
Master's degree in software engineering, data engineering, computer science, or related field.
Over 3 years of hands-on professional experience in data engineering, specifically developing and maintaining data pipelines on AWS, Azure and/or Databricks.
Strong proficiency with AWS, GitLab, Databricks (ETL), Airflow, SCL, Python, Scala, DBT, AWS CDK, and Terraform.
Work Experience Required: Over 3 years in data engineering roles with multi-cloud environments.
Experienced in implementing Lakehouse architecture with Databricks and Delta Lake, including medallion architecture for data quality and reusability.
Practical knowledge of enterprise data sources such as SAP ERP, Salesforce, and Product Data Management systems.
Demonstrated ability to work in global, multicultural agile teams, adopting DevOps and DataOps practices with strong accountability and problem-solving skills.