Data Engineer - KT

What Will You Do? · Data Pipeline Infrastructure & Architecture o Design and implement scalable data architectures on cloud data platforms with high availability, security, and performance o Lead development of Data Lakehouse solutions o Collaborate with stakeholders to understand requirements and translate them into technical specifications

· Pipeline Development & Optimisation o Build and maintain robust ETL/ELT pipelines using modern data engineering tools and frameworks o Optimise data processing workflows for performance, cost-effectiveness, and reliability o Implement automated data quality checks and monitoring systems to ensure data integrity

· Data Systems Architecting & Solutioning o Design and architect comprehensive cloud-native Data & AI solutions aligned with business objectives and technical requirements o Lead cloud migration strategies and oversee implementation of complex multi-cloud environments o Drive innovation through integration of Data & AI capabilities into HDB’s Data & AI platform product architectures o Conduct technical assessments and recommend modernised approaches using cloud native technologies o Maintain architectural documentation

· Cloud Platform Operations o Leverage Cloud Native Services to build and manage data infrastructure o Implement infrastructure as code practices using Terraform o Ensure compliance with security standards and data governance policies

· Technical Leadership & Collaboration o Mentor junior data engineers and provide technical guidance on complex challenges o Participate in architectural reviews and contribute to data strategy evolution

You 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 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 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 platforms

Working Location : Central

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