Senior Lead Data Engineer, Data Products To join the team developing modern cloud data architecture based data products for a KONE. Our Data Foundation based data products are key enabler in our digital transformation creating ability to develop new scalable analytics, AI and digital use cases by leveraging data across the whole KONE organization. Data products play a vital role in business value generation and driving optimized data architecture is crucial to ensure reusability of the data assets on the cloud based Data Foundation. This is a hands-on, roll up your sleeves position that requires a passion for data, engineering and DevOps. In this role you will be doing hands on data engineering tasks from new development to resolving technical issues, maintaining and optimizing workloads. As a Lead Data Engineer, in addition to doing hands-on data engineering work in the data product team, we expect you to demonstrate in-depth domain-specific knowledge, critically evaluating new data-engineering methods and applying them, being responsible for deliverables to be implemented with industry best practices and aligned with the design and architecture principles, being responsible for ensuring that Data Engineers follow agreed development process and fagreed CI/CD principles, being responsible for planning and conducting quality actions such as code reviews, triages in the team. We offer a chance to work hands-on with state-of-the-art cloud technology in a global, multi-cultural work environment being located in our office in Chennai. We approach multi-cloud data engineering experience, as your professional background. We are searching for an enthusiastic person to join the team who is excited about developing own professional skills even further, learning new things and contributing to team success. An ideal candidate has a strong background in data engineering, SW engineering and data integration with modern multi cloud stack, but above all will to commit to a DevOps mindset and reach goals together. We are expecting you to take self-driven, proactive approach to your work, find & implement solutions, continuously looks for improvement opportunities in own area, solve problems, make decisions and share the learnings to colleagues. We want to work with people who enjoy teamwork, are not afraid to step out of their comfort zone, want to help others and share information. To succeed in this role, following professional experience will play a key role: Master's degree in either software engineering, data engineering, computer science, or a related field Hands-on data engineering professional experience (> 5 years) Previous hands-on professional experience in developing and maintaining data pipelines on AWS, Azure and/or Databricks. Working proficiency the the tech stack: AWS, Gitlab, Databricks for ETL, Airflow, SCL, Python, Scala, and DBT for developing ETL, jobs, AWS CDK and Terraform for IaC. Hands-on development experience on lake house architecture based on Databricks and Delta Lake, multi-hop medallion architecture to divide the data lake into bronze, silver and gold layers based on the quality and reusability of the data stored there, data product publishing in Unity catalog. Strong coding proficiency with multiple languages SQL and Python, additional language are bonus. Ability to write compelling code, technical documentation and visualize your technical design. Fluency in industry-standard DevOps practices and tools. Practical experience in working with enterprise data landscapes and data structures: Structural data, non-structural data, metadata, master data, transactional data, batch/NRT. Experience on enterprise data sources: Experience in woring with e.g. SAP ERP, Salesforce, Droduct data management (PDM), and many others. Way of working professional experience Passion to utilize agile development methodologies and tools (Jira, Confluence, draw.io). Inbuilt cybersecurity awareness. Understanding on data privacy and compliancy regulations. Ability to work in global multi-cultural team and effectively collaborate within the team. Ability to self-organize, take accountability and be proactive, seek feedback, be courageous and resilient, and have excellent problem-solving skills. Ability to conduct technical evaluations and feasibility studies. Ability to mentor and share knowledge as an expert leader. Experience of DataOps and ITSM processes. Proficiency in spoken and written English language, and strong facilitation and communication skills.
