3 months ago
Pune, IndiaStaff+
Responsibilities
- Design data pipelines and perform hands-on data engineering development for data product teams.
- Translate business needs into technical requirements and industrialize, optimize, and maintain production-grade data pipelines.
- Apply architecture guardrails, design principles, quality practices, code reviews, and triage processes.
- Promote reusable design patterns and maintainable data products while identifying and managing technical debt.
- Plan production and support operations, troubleshoot incidents, identify root causes, and implement improvements.
- Use performance metrics and data consumer feedback to identify improvement opportunities and optimize cloud costs.
- Define common data engineering practices and lead organization-wide capability development when assigned.
- Provide technical advisory to business stakeholders and represent KONE in technology forums and university collaborations.
- Lead Data Engineers, mentor and coach colleagues, conduct training, and mature DataOps practices.
Requirements
- Master’s or PhD degree in computer science, software engineering, statistics, mathematics, data science, machine learning, or another quantitative field.
- 18–20 years of professional hands-on experience in data engineering and software engineering.
- Proven experience developing industrial-grade, reusable data products and production data pipelines using cloud technology.
- Technical expertise with Databricks data engineering, Unity Catalog, Airflow, dbt, AWS Glue, AWS EMR, AWS Athena, Spark, Apache Flink, Apache Kafka, Terraform, and GitLab or GitHub.
- Strong hands-on coding ability in Python, SQL, and Scala across the full data product and data pipeline lifecycle.
- Experience with software development lifecycle methods, DevSecOps/DataOps practices, cybersecurity guidelines, data privacy, compliance regulations, quality assurance, and cloud FinOps.
- Experience working with complex enterprise data landscapes and systems such as IoT, SAP ERP, Salesforce, PDM, and MES.
- Experience coaching or mentoring engineers, leading teams, sharing knowledge, and improving DataOps practices.
- Ability to write technical documentation, visualize technical designs, collaborate across global multicultural teams, and communicate effectively in English.
- Databricks and AWS certifications are preferred.
- Experience with Agile development methodologies and tools such as Jira, Confluence, and draw.io is expected.
Benefits
- Innovative and collaborative working culture that values individual contributions, employee engagement, and knowledge sharing.
- Opportunities for professional development, learning, mentoring, and contributing to digital transformation initiatives.
- KONE promotes ethical business practices, sustainability, teamwork, trust, respect, and recognition of good performance.
- The company offers experiences and opportunities intended to support career and personal goals and a healthy, balanced life.
Tech Stack
Categories
Data Engineering
About KONE
KONE designs, manufactures, installs, and services elevators, escalators, and automatic building doors for commercial, residential, and infrastructure customers. Its business combines equipment sales with long-term maintenance and modernization services to keep buildings operating reliably. Founded in 1910 and headquartered in Espoo, Finland, KONE is a public company with global operations serving property developers, building owners, and transit operators.