Senior Tech Lead

Virtusa; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Virtusa in Singapore is seeking a Python-focused Data Engineer to design and maintain scalable data pipelines, process large datasets, and enable AI/Generative AI applications through well-structured data infrastructure.

You will build reusable Python modules for ingestion, perform EDA, optimize workflows for performance, support data needs for AI/ML, and develop data services or APIs to power downstream AI applications, with emphasis on data quality and observability.

Qualifications

• Strong Python experience with data tooling.
• Hands-on with pandas and NumPy.
• Experience with SQL for data extraction.
• Familiarity with ML workflows and model evaluation.
• Experience with AI/Generative AI enablement.
• Cloud familiarity (AWS/GCP/Azure) preferred.

Responsibilities

• Build scalable data pipelines and data-intensive systems.
• Process large datasets and ensure data quality.
• Develop reusable Python modules for ingestion and automation.
• Perform EDA to understand data patterns and quality issues.
• Support AI/ML data requirements and integrate AI models into pipelines.
• Expose data services/APIs for downstream AI applications.

Skills

Python

Data pipelines

SQL

EDA

Pandas

NumPy

Matplotlib

PyTorch

AI/Gen AI enablement

Tools

pandas

NumPy

Matplotlib

scikit-learn

PyTorch

LangChain

AutoGen

CrewAI

OpenAI

Anthropic

LLaMA

Mistral

Job description

Python-focused Data Engineer with strong hands-on coding skills in data-intensive systems. The role focuses on building scalable data pipelines, processing large datasets, and enabling AI/Generative AI applications through well-structured data infrastructure.Use data analysis and manipulation tools to handle large datasets efficientlyDevelop reusable Python modules for data ingestion and pipeline automationPerform exploratory data analysis (EDA) to understand data patterns and quality issuesOptimize data workflows for performance, scalability, and reliabilitySupport data requirements for AI/ML and Generative AI systemsBuild data services and APIs to support downstream AI applicationsEnsure data quality, consistency, and observability across pipelines

Required Python & Data Libraries (Hands-on Experience Mandatory)

• Candidates must have strong practical experience with pandas — data manipulation, transformation, and analysis
• NumPy — numerical operations and array-based processing
• Matplotlib — data visualization and reporting
• scikit-learn — basic ML workflows and model evaluation
• PyTorch — deep learning and AI model experimentation
• AI / Generative AI Enablement
• Prepare and structure datasets for ML and LLM-based systems
• Support integration of AI models into data pipelines and applications
• Enable workflows for Generative AI use cases (RAG systems, agent workflows)
• Work with multiple AI model providers
• OpenAI
• Anthropic
• LLaMA
• MistralExposure to AI orchestration frameworks such as LangChain, AutoGen, and CrewAI
• Core Strong SQL skills for data extraction and manipulation
• Understanding of data modeling and analytics workflows
• Ability to support end-to-end data-to-AI pipelines
• Preferred / Good to Have
• Experience with big data or distributed processing systems
• Understanding of vector databases and embedding-based retrieval systems
• Experience building APIs or services for data/AI systems
• Familiarity with cloud platforms (AWS, Azure, GCP)
• Exposure to production monitoring and data observability tools
• Python, ETL, SQL
• Pandas
• Nympy
• Matplotlib
• scikit-learn
• PyTorch
• Open AI
• Anthropic
• LLaMA
• Mistral
• AI orchestration frameworks such as LangChain, AutoGen, and CrewAI
• DB ( SQL, No SQL, Oracle)
• GCP
• AWSAPI
• Data Systems