Senior Data Engineer (AI & ML)

We are looking for highly skilled and experienced professionals for the role of Senior Data Engineer (AI & ML) 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. 

General Responsibilities

• Collaborate with architects, business teams, analysts, and engineering teams. 
• Provide technical leadership and mentoring to junior engineers and data scientists. 
• Participate in architecture discussions, code reviews, and technical governance. 
• Support cloud migration, modernization, and digital transformation initiatives. 
• Prepare technical documentation, solution designs, and implementation plans. 
• Ensure adherence to security, privacy, and regulatory compliance standards. 

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: 

• TensorFlow / PyTorch / Scikit-learn 

  ML pipelines and MLOps frameworks 

  Model monitoring and optimization 

• Understanding of AI governance, explainability, and responsible AI practices. 

Cloud & DevOps

• Experience with cloud platforms such as: 

• AWS 

  Azure 

  GCP 

• Knowledge of: 

• Docker 

  Kubernetes 

  CI/CD pipelines 

  Infrastructure automation 

Government/Public Sector Experience (Preferred)

• 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.