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

**We regret to inform that only shortlisted candidates will be notified. Personal data collected will be used for recruitment purposes**