About this role
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.
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