Data Engineer - KT

What Will You Do?· Data Pipeline Infrastructure & Architectureo Design and implement scalable data architectures on cloud data platforms with high availability, security, and performanceo Lead development of Data Lakehouse solutionso Collaborate with stakeholders to understand requirements and translate them into technical specifications· Pipeline Development & Optimisationo Build and maintain robust ETL/ELT pipelines using modern data engineering tools and frameworkso Optimise data processing workflows for performance, cost-effectiveness, and reliabilityo Implement automated data quality checks and monitoring systems to ensure data integrity· Data Systems Architecting & Solutioningo Design and architect comprehensive cloud-native Data & AI solutions aligned with business objectives and technical requirementso Lead cloud migration strategies and oversee implementation of complex multi-cloud environmentso Drive innovation through integration of Data & AI capabilities into HDB’s Data & AI platform product architectureso Conduct technical assessments and recommend modernised approaches using cloud native technologieso Maintain architectural documentation· Cloud Platform Operationso Leverage Cloud Native Services to build and manage data infrastructureo Implement infrastructure as code practices using Terraformo Ensure compliance with security standards and data governance policies· Technical Leadership & Collaborationo Mentor junior data engineers and provide technical guidance on complex challengeso Participate in architectural reviews and contribute to data strategy evolutionYou will be a Great Fit If You Have· Bachelor’s degree in computer science, Information Technology, Computer Engineering, or related field· Minimum 4 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 technologiesGood 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 SageMaker 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 visualisation tools and business intelligence platformsWorking Location : Central**We regret to inform that only shortlisted candidates will be notified. Personal data collected will be used for recruitment purposes**