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Popular mid-level Data Engineer role in metro Pune with broad cloud requirements increases candidate competition.
Enterprise Databricks and SAP integration focus moderately limits cross-industry transferability.
Multiple mandatory technologies and >3 years' experience make shortlisting highly selective.
Develop, maintain, and optimize cloud-based data pipelines and data products that enable scalable analytics, AI, and digital use cases for KONE's Data Foundation.
Implement and manage lake house architecture (Databricks, Delta Lake) including multi-hop medallion layers and data product publishing in Unity catalog to ensure data reusability and quality.
Apply DevOps practices in data engineering tasks including infrastructure as code (AWS CDK, Terraform) and continuous integration (Gitlab) within a multi-cloud environment.
Master's degree in software engineering, data engineering, computer science, or related field.
Over 3 years of hands-on professional experience in data engineering, developing and maintaining data pipelines on AWS, Azure, and/or Databricks.
Technical proficiency with AWS, Gitlab, Databricks (ETL), Airflow, SCL, Python, Scala, DBT, AWS CDK, Terraform and lake house architecture based on Databricks and Delta Lake.
Proficiency in SQL and Python; experience with enterprise data sources (e.g., SAP ERP, Salesforce) and familiarity with data privacy and security compliance.
Experienced data engineer with strong software engineering and data integration skills in multi-cloud environments, especially using Databricks and AWS/Azure.
Practices DevOps mindset with proven ability to take ownership, solve problems proactively, and continuously improve data architecture and pipelines.
Works effectively in global multi-cultural teams, demonstrates agility with modern development tools and data governance, and maintains strong communication and collaboration skills.