Dear Candidate,
We are looking for highly skilled and experienced professionals for the role of Senior Data Engineer / Senior AI & ML Engineer with strong expertise in enterprise data platforms, artificial intelligence, machine learning, and large-scale analytics solutions. The ideal candidate should possess deep technical knowledge in modern data engineering and AI/ML ecosystems, along with experience delivering scalable and secure solutions for government or public sector programs. The role requires hands-on engineering expertise, architecture understanding, and the ability to work across complex data transformation and AI-driven initiatives.
Key Responsibilities
Data Engineering Responsibilities
- Design, develop, and maintain scalable data pipelines and enterprise data platforms.
- Build robust ETL/ELT frameworks for structured and unstructured data processing.
- Develop and optimize data ingestion, transformation, and integration workflows.
- Implement data lakes, data warehouses, and real-time streaming architectures.
- Ensure data quality, governance, security, lineage, and compliance standards.
- Work with large-scale datasets from multiple enterprise and government systems.
- Optimize data storage, processing performance, and scalability.
AI/ML Responsibilities
- Design, develop, train, and deploy machine learning and AI models for enterprise use cases.
- Build predictive analytics, NLP, computer vision, recommendation systems, or intelligent automation solutions.
- Implement MLOps practices for model deployment, monitoring, retraining, and governance.
- Collaborate with business and domain teams to translate requirements into AI-driven solutions.
- Evaluate emerging AI technologies and recommend modernization strategies.
- Develop responsible AI frameworks aligned with governance and compliance requirements.
Job Requirements:
· Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related field.
- 8+ years of hands-on experience in Data Engineering and AI/ML practices.
- Data Engineering- Strong expertise in: Python ,SQL ,Spark / PySpark ,Hadoop ecosystem ,ETL/ELT pipelines ,Data Warehousing concepts
- Experience with: Apache Kafka ,Airflow ,Databricks ,Snowflake ,Big Data technologies
- Strong knowledge of batch and real-time data processing.
· AI/ML Engineering: Hands-on experience in: Machine Learning algorithms ,Deep Learning frameworks ,NLP and Generative AI concepts ,Model training and deployment
- Experience with: ensorFlow / PyTorch / Scikit-learn ,ML pipelines and MLOps frameworks ,Model monitoring and optimization
- Understanding of AI governance, explainability, and responsible AI practices.
- Experience with cloud platforms such as: AWS ,Azure ,GCP
- Knowledge of: Docker ,Kubernetes ,CI/CD pipelines ,Infrastructure automation
- Experience working on Government/Public Sector digital transformation projects.
- Understanding of governance, compliance, security, and large-scale citizen data systems.
- Exposure to smart governance, public administration, e-governance, or national-scale platforms is an advantage.
Preferred Skills
- Experience with GenAI, LLMs, Retrieval-Augmented Generation (RAG), or AI copilots.
- Familiarity with graph databases and knowledge graphs.
- Exposure to data governance and metadata management tools.
- Experience with BI and analytics platforms such as Power BI or Tableau.
- Certifications in Cloud, Data Engineering, or AI/ML are preferred.
