Senior Data Engineer

Bachelor’s degree in computer science, Information Technology, Computer Engineering, or related field Minimum 3 years of relevant experience in data systems architecture, data systems integration, and data pipeline setup at production scale Good understanding of cloud computing principles including infrastructure as code, containerisation, microservices architecture, cloud security frameworks, identity and access management, network architecture, and distributed systems Proven ability to translate business requirements into technical solutions Excellent communication skills for presenting complex concepts to diverse audiences Experience with cloud security frameworks, compliance requirements, and risk management Experience in data domains (e.g. DataOps, Data Lakehouse) and AI/ML Domains (e.g. MLOps, LLMOps) Strong Knowledge and Hands-on experience with SQL, Python and Apache Spark Hands-on experience with Apache Kafka, Airflow, or similar technologies Good to Have: Proficiency in Amazon Web Services (AWS) services Relevant cloud certifications (e.g. AWS Solutions Architect Professional, AWS Data Engineer Associate) would be an advantage Experience with Data & AI cloud-native services (e.g. Amazon Sage Maker Unified Studio, Amazon Quick Suite, AWS S3, AWS Glue, AWS Lake Formation, AWS Bedrock, AWS Agent Core). Familiarity with serverless computing, edge computing, and IoT architectures would be an advantage. Experience with machine learning operations (MLOps) and ML model deployment pipelines Knowledge of data governance frameworks and metadata management tools Familiarity with data visualization tools and business intelligence platforms