Senior Data Consultant

Key responsibilities• Design, develop, and optimize scalable ETL pipelines for structured andunstructured data.• Build and maintain big data processing workflows using PySpark, Scala, and AWSEMR.• Develop data integration pipelines using Azure Data Factory, AWS Glue, and similartools.• Design, develop, and deploy machine learning models using Scikit-learn,TensorFlow, and PyTorch.• Build and maintain data warehouse and analytics solutions using AWS Redshift,PostgreSQL, MySQL, MongoDB, and S3.• Develop backend services and RESTful APIs using Python frameworks and Node.js.• Implement DevOps best practices using Docker, Jenkins, RabbitMQ, SonarQube,Celery, and CI/CD pipelines.• Lead code reviews, mentor team members, and support Proof of Concept (POC)initiatives.• Collaborate with clients and stakeholders to deliver scalable, production-ready datasolutions.Core Competencies Required• 7+ years of professional experience in data engineering with exposure to machinelearning and cloud platforms.• Expert proficiency in Python; working knowledge of JavaScript, Shell, Scala, andTypeScript.• Strong experience with PySpark, Scala, and distributed data processing on AWS EMRor similar platforms.• Hands-on experience with AWS services (EMR, Lambda, S3, Redshift, EC2) and AzureData Factory; exposure to GCP is an advantage.• Proficiency in relational and NoSQL databases, including PostgreSQL, MySQL, MongoDB,and Redis.• Experience with machine learning frameworks and libraries such as Pandas, Scikit-learn, TensorFlow, and PyTorch.• Strong knowledge of Docker, Jenkins, SonarQube, Celery, RabbitMQ, and CI/CDpractices.• Experience deploying production applications using Gunicorn, Apache, or NGINX.• Excellent communication, leadership, mentoring, and stakeholder management skills.• Experience with healthcare, pharmaceutical, or fintech data platforms is an advantage.• Exposure to computer vision, NLP, recommendation systems, or web automationtechnologies is preferred.