Principal Data Engineer, Data Products

Role & responsibilities

to join KONE IT Enterprise Data & Analytics team in Pune, India. The team is driving forward Data Foundation, new way of working with data using latest cloud technology. Data Foundation is key enabler in our digital transformation creating ability to develop new scalable analytics, AI and digital use cases by leveraging data across the whole organization. In our approach, data products play a vital role in business value generation. Driving optimized data engineering practices is crucial to ensure reusability and maintainability of the data products.

Principal Data Engineer leads the design, development, and industrialization of data pipelines to provide industrial grade data products for our data consumers. With the deep deep technical knowledge, Principal Data Engineer does hands on development of data products of significant complexity using applicable best practices. S/he acts as the go-to-person on the technical aspects for data product teams. S/he proactively identifies and drives the adoption of both new innovations and best practices for adopting these at an industrial scale to deliver optimized and high performing data pipelines.

Principal Data Engineer has strong communication skills to be able to translate the data requirements into technical requirements. S/he drives the delivery quality by ensuring appropriate development and quality practices are followed. Principal Data Engineer follows the technological progress, drives the definition of the common data engineering practises and ensures the best way of working by the teams. As subject matter expert in the discipline, s/he conducts trainings and provides guidance to others on data engineering practises, technology and/or development methods demonstrating strong communication, mentoring and coaching skill. Principal Data Engineer acts also as a people manager for experts within the discipline.

We are searching for an enthusiastic person to join the team who is excited about developing his/her own professional skills even further, learning new things and contributing to team success. We are expecting you to take a self-driven, proactive approach to your work, find & implement solutions, solve problems, 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.

Key responsibilities:

• Designing data pipelines and doing hands-on data engineering development tasks in product teams. Understanding the business needs, data, methods for industrializing the data pipelines, their optimization and limitations.
• Demonstrating in-depth business domain-specific knowledge, ensuring that data pipelines are implemented with industry best practices, aligned with the design principles and architecture guardrails including planning and conducting quality actions, such as code reviews and triages in the teams.
• Maximizing reusability and usage of common design patterns across the data product teams with an aim to keep them lean and maintainable. Identifying technical debt regularly and ensuring that its management is prioritized in the product backlogs.
• Planning the production and support operations for data pipelines to be deployed for data consumers, troubleshooting and resolving incidents and identifying root causes and resolving them when needed. Identifying improvement opportunities based on the performance metrics and data consumer feedback.
• When agreed, takes additional responsibilities, such as leading organization wide capability development, engage with business stakeholders to provide data engineering and technology related advisory, representing KONE in internal and external forums such as technology forums, university collaboration etc.
• Team lead for Data Engineers.

To succeed in Principal Data Engineer role, following professional experience will play a key role:

• Master's or PhD degree in a quantitative field, for example computer science, sw engineering, statistics, mathematics, or data science/machine learning.
• Proven track record in applying data engineering practices to develop industrial grade reusable data products using cloud technology, industrializing data pipelines to production grade solutions and continuously improving them.
• 15-20 years of professional hands-on experience in data engineering and software engineering.
• Technical expertise in following tech stack: Databricks data engineering, Unity Catalog, Airflow, DBT, AWS Glue, AWS EMR, AWS Athena, Spark, Apache Flink, Apache Kafka, Terraform, Gitlab/Github. Databricks and AWS certifications preferred.
• Outstanding coding skills with multiple languages (Python, SQL, Scala) with proven hands-on experience in industry standard software development life cycle methods, DevSecOps/DataOps practices spanning the full data product/data pipeline lifecycle.
• Expertise in cybersecurity guidelines, data privacy, compliancy regulations and quality assurance practices, and cloud FinOps.
• Ability to write clear technical documentation and visualize your technical design.
• Practical experience in working with complex enterprise data landscapes and data structures (IoT and main enterprise systems such as SAP ERP, Salesforce, PDM, MES, etc.) and continuously optimize cloud costs.
• Experience in coaching and/or mentoring, leading teams, sharing knowledge and maturing DataOps practices.
• Passion to utilize agile development methodologies and tools (Jira, Confluence, draw.io).
• Ability to work in global multi-cultural team across different countries and effectively collaborate within the teams.
• Ability to self-organize and be proactive, seek feedback, be courageous and resilient, and have excellent problem-solving skills.
• Proficiency in spoken and written English language, and strong facilitation and communication skills