Overview
At Xtremax, we help government agencies and enterprises build robust, scalable, and future-ready digital systems. As a Senior Data Engineer, you will play a key role in designing scalable data architectures, translating business requirements into robust technical specifications, and building high-performance data pipelines. This role combines technical leadership, data systems solutioning, and stakeholder collaboration to deliver impactful, data-driven digital solutions. Candidates with public sector experience are preferred, as this role supports IT projects for government agencies.
Responsibility:
- Data Pipeline Infrastructure & Architecture
- Design and implement scalable data architectures on cloud data platforms with high availability, security, and performance
- Lead development of Data Lakehouse solutions
- Collaborate with stakeholders to understand requirements and translate them into technical specifications
- Pipeline Development & Optimisation
- Build and maintain robust ETL/ELT pipelines using modern data engineering tools and frameworks
- Optimise data processing workflows for performance, cost-effectiveness, and reliability
- Implement automated data quality checks and monitoring systems to ensure data integrity
- Data Systems Architecting & Solutioning
- Design and architect comprehensive cloud-native Data & AI solutions aligned with business objectives and technical requirements
- Lead cloud migration strategies and oversee implementation of complex multi-cloud environments
- Drive innovation through integration of Data & AI capabilities into enterprise platform architectures Data & AI platform product architectures
- Conduct technical assessments and recommend modernised approaches using cloud native technologies
- Maintain architectural documentation
- Cloud Platform Operations
- Leverage Cloud Native Services to build and manage data infrastructure
- Implement infrastructure as code practices using Terraform
- Ensure compliance with security standards and data governance policies
- Technical Leadership & Collaboration
- Mentor junior data engineers and provide technical guidance on complex challenges
- Participate in architectural reviews and contribute to data strategy evolution
Requirements:
- 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 (Optional):
- Proficiency in Amazon Web Services (AWS) ecosystem and relevant cloud certifications (e.g., AWS Solutions Architect Professional, AWS Data Engineer Associate).
- Hands-on experience with Data & AI cloud-native services (e.g., Amazon SageMaker, AWS S3, AWS Glue, AWS Lake Formation, AWS Bedrock).
- Familiarity with MLOps, ML model deployment pipelines, serverless computing, edge computing, or IoT architectures.
- Knowledge of metadata management tools, data governance frameworks, or business intelligence / data visualization tools (e.g., Power BI, Tableau).