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Mid-level, popular Data Engineer role in a metro with broad cloud/Databricks requirements increases applicant competition.
Technical data engineering skills are transferable but enterprise systems experience (SAP, Salesforce) creates moderate domain bias.
Multiple mandatory technologies, cloud/Databricks experience and explicit 3+ year requirement make screening fairly strict.
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Develop and maintain Data Foundation based data products enabling scalable analytics, AI, and digital solutions across KONE.
Handle hands-on data engineering tasks including new development, issue resolution, workload maintenance, and optimization using multi-cloud technology.
Ensure optimized and reusable data architecture on cloud platforms utilizing lake house and medallion architecture principles.
Master's degree in software engineering, data engineering, computer science, or related field.
Over 3 years of hands-on data engineering experience.
Proficiency in AWS, Azure, Databricks, GitLab, Airflow, SCL, Python, Scala, DBT, AWS CDK, and Terraform with multi-cloud data pipeline development and maintenance experience.
Work Experience Required: More than 3 years of professional data engineering experience.
Strong coding skills in SQL and Python with experience in multi-language environments and writing technical documentation.
Experienced in DevOps practices, agile methodologies, DataOps, ITSM processes, and working in enterprise data landscapes with data types like structural, non-structural, metadata, and transactional data.
Comfortable working in a global multicultural team, proactive in problem-solving, self-organization, and continuous improvement mindset.