We're looking for a Senior Data Engineer to design, build, and optimise scalable data platforms that support analytics, AI/ML, and smart manufacturing initiatives. You'll lead the development of batch, streaming, and event-driven data pipelines while working closely with business stakeholders and engineering teams to deliver reliable, cloud-native data solutions.

Responsibilities

• Design and develop scalable ETL/ELT, streaming, and event-driven data pipelines.
• Build and maintain cloud-based data platforms, data warehouses, and Lakehouse architectures.
• Develop data solutions using Python, SQL, Apache Spark, Airflow, Kafka, and modern cloud technologies.
• Implement DataOps best practices, including CI/CD, monitoring, testing, and pipeline optimisation.
• Collaborate with cross-functional teams to translate business requirements into technical solutions and mentor junior engineers.

Requirements

• 8+ years of experience in Data Engineering, Data Warehousing, or large-scale data platform development.
• Strong hands-on experience with Python, SQL, Apache Spark, Airflow, Kafka, and modern cloud data platforms such as Databricks, Snowflake, BigQuery, Redshift, or Azure Synapse.
• Experience with AWS, Azure, or GCP, Lakehouse architectures, and DataOps/CI/CD practices.
• Strong understanding of data modelling, database design, and performance optimisation.
• Experience with Industrial IoT (IIoT), MES, PLC, SCADA, or manufacturing data systems is highly preferred.