Senior Data Consultant

About the Role

About Us

Bridge BSS Talent is a global leader in IT outsourcing and business support services. We

empower businesses with cutting-edge AI solutions, scalable cloud infrastructure, and

elite tech talent. Our teams work with some of the world’s most innovative companies to

deliver measurable impact through technology.

We are looking for a Senior Data Consultant with 7+ years of experience spanning data

engineering, machine learning, and cloud computing to design, build, and scale data

platforms for our global clients. The ideal candidate has a strong track record of

architecting ETL pipelines, deploying predictive models, and leading cross-functional

delivery in pharmaceutical, fintech, SaaS, and enterprise domains. This role combines

hands-on data engineering, ML application, and team leadership within an agile delivery

model.

Key Responsibilities

• Design, develop, and optimize scalable ETL pipelines for structured and unstructured data.

• Build and maintain big data processing workflows using PySpark, Scala, and AWS EMR.
• Develop data integration pipelines using Azure Data Factory, AWS Glue, and similar tools.
• 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 data solutions

Requirements

• 7+ years of professional experience in data engineering with exposure to machine learning and cloud platforms.

• Expert proficiency in Python; working knowledge of JavaScript, Shell, Scala, and TypeScript.

• Strong experience with PySpark, Scala, and distributed data processing on AWS EMR or similar platforms.

• Hands-on experience with AWS services (EMR, Lambda, S3, Redshift, EC2) and Azure Data 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, Scikitlearn, TensorFlow, and PyTorch.

• Strong knowledge of Docker, Jenkins, SonarQube, Celery, RabbitMQ, and CI/CD practices.

• 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 automation technologies is preferred