Data Engineer & AI Tech Lead - Contract Role
Hands-on contract role in Singapore leading data platform delivery for a strategic energy-sector client: designing pipelines and lakehouse architecture on Azure Databricks and Microsoft Fabric with Python, PySpark and SQL, while building AI/LLM-powered solutions, APIs, backend services, and providing technical leadership.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Contract
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Strong professional experience in data engineering, designing and implementing enterprise-scale data platforms
- Proven experience with Microsoft Azure, Azure Databricks, and Microsoft Fabric
- Strong programming skills in Python and experience with PySpark and SQL
- Experience building and maintaining complex ETL/ELT pipelines and data integration solutions
- Good understanding of data lakehouse architecture, data warehousing, data modelling, and distributed data processing
- Experience with Azure services for data storage, orchestration, integration, and analytics
- Practical knowledge of AI/ML concepts and experience developing or integrating AI-powered solutions
- Experience developing REST APIs, backend services, and software integrations
- Familiarity with CI/CD pipelines, Git, automated testing, and DevOps practices
- Strong analytical, troubleshooting, and problem-solving skills
- Excellent communication skills and ability to engage directly with client stakeholders
- Ability to work independently, take ownership, and deliver in a dynamic client environment
Full description
We are looking for a versatile, hands-on Data Engineer & AI Tech Lead to work with a strategic energy client in Singapore. The role focuses on designing, building, and evolving the client's data platform using Databricks and Microsoft Fabric on Microsoft Azure, while extending into AI engineering, software development, and business process automation.
This role requires a strong combination of technical expertise, architectural thinking, and problem-solving skills. You will work closely with client stakeholders to understand business challenges, design scalable solutions, and deliver them end to end—from data pipelines and platform architecture to AI-driven applications, APIs, and automation.
As a trusted technical partner to the client, you will take ownership of complex technical challenges, recommend the right solutions, and drive implementation while ensuring quality, scalability, security, and business value.
Key Responsibilities1. Data Engineering & Platform Development
- Design, build, and maintain scalable data platforms and pipelines using Azure Databricks and Microsoft Fabric.
- Develop robust ETL/ELT pipelines to ingest, transform, process, and integrate data from multiple sources.
- Implement data lakehouse architectures, data modelling, and data transformation frameworks.
- Work with Python, PySpark, and SQL to process large datasets efficiently.
- Establish data quality checks, validation frameworks, monitoring, and error-handling mechanisms.
- Optimise data pipelines, queries, and platform performance while managing costs.
- Implement data governance, security, access controls, and best practices for enterprise data management.
2. AI & Machine Learning Engineering
- Identify opportunities to apply AI, machine learning, and generative AI to address business challenges.
- Design and develop AI-powered solutions, including intelligent applications, predictive models, and workflow automation.
- Integrate AI capabilities into existing data platforms and business applications.
- Work with large language models (LLMs), retrieval-augmented generation (RAG), and AI orchestration frameworks where applicable.
- Develop proof of concepts and translate successful experiments into production-ready solutions.
- Evaluate AI solutions for accuracy, reliability, scalability, security, and business impact.
3. Software Engineering & API Development
- Design, develop, and maintain APIs, backend services, and applications to support business requirements.