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.