Chemelex is a global leader in electric thermal and sensing solutions, protecting the world’s critical processes, places and people. With over 50 years of innovation and a commitment to excellence, we develop solutions that ensure safety, reliability, and efficiency in diverse environments – from industrial plants and data centers to people’s homes. We deliver future-ready technologies, advanced engineering capabilities and local expertise backed by global standards. Our offering includes a leading portfolio from our trusted brands: Raychem, Tracer, Nuheat and Pyrotenax.
Job Summary
We are seeking a talented and self-driven Data Systems Technologist to design, implement, and optimize robust data systems across Chemelex’s software portfolio. This role focuses on advancing cloud-based and industrial IoT (IIoT) data architectures to enable real-time analytics, seamless system integration, and insightful business intelligence. You will collaborate across cross-functional teams in a hybrid work environment, ensuring scalable, reliable, and high-performance data infrastructure.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL frameworks to support enterprise-wide data initiatives.
• Develop and implement data management solutions across cloud and on-premises IIoT environments.
• Collaborate with software engineers, system architects, and business stakeholders to define data architecture and integration requirements.
• Research and integrate modern data technologies (e.g., lake house, streaming, edge computing) to improve feature sets, reduce operational costs, and enhance service quality.
• Enforce data governance, security, validation, and monitoring protocols to maintain high data quality and system integrity.
• Incorporate DevOps principles and CI/CD practices into data engineering workflows.
• Embrace a culture of inclusion, innovation, and continuous improvement.

Required Qualifications

• Bachelor’s degree or higher in Computer Science, Computer Engineering, Data Engineering, or a related field; or equivalent hands-on experience.
• 2+ years of professional experience in data engineering, database development, or data application development.
• Proficient in SQL, DQL, DMQL, or equivalent query languages.
• Experience with modern data platforms such as Snowflake, Redshift, BigQuery, or equivalent.
• Proven experience in deploying and managing data workloads in cloud environments (e.g., Azure, AWS).
• Understanding and application of DevOps principles within data environments.
• Familiarity with Agile, Scrum, or Lean software development methodologies.
• Exposure to multiple programming languages (e.g., Python, Java, Scala).
• Working knowledge of source control, ticketing, and collaboration tools (e.g., Git, GitLab, Jira, Confluence).
• Experience working with relational databases such as PostgreSQL, MySQL, SQL Server.

Preferred Qualifications

• Experience with real-time or near-real-time data processing tools (e.g., Apache Kafka, Spark Streaming, Flink).
• Familiarity with containerization and orchestration (Docker, Kubernetes).
• Knowledge of NoSQL databases (e.g., MongoDB, Cassandra).
• Contributions to open-source projects or participation in data communities.

• Design, build, and maintain scalable data pipelines and ETL frameworks to support enterprise-wide data initiatives.
• Develop and implement data management solutions across cloud and on-premises IIoT environments.
• Collaborate with software engineers, system architects, and business stakeholders to define data architecture and integration requirements.
• Research and integrate modern data technologies (e.g., lake house, streaming, edge computing) to improve feature sets, reduce operational costs, and enhance service quality.
• Enforce data governance, security, validation, and monitoring protocols to maintain high data quality and system integrity.
• Incorporate DevOps principles and CI/CD practices into data engineering workflows.
• Embrace a culture of inclusion, innovation, and continuous improvement