1 hour 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
