Data Engineer

 Develop high-quality Python applications following software engineering best practices.

• Perform code reviews, unit testing, integration testing, and performance testing.
• Maintain technical documentation, architecture diagrams, and deployment standards.
• Participate actively in Agile ceremonies including sprint planning, backlog refinement, and retrospectives.
• Drive continuous improvement initiatives across data engineering and MLOps practices.
• Experience implementing DataOps, MLOps, and observability solutions.
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  •        Data Engineering & Platform Development
• Design, build, and maintain scalable batch and real-time data pipelines.
• Develop robust ETL/ELT frameworks for ingesting, transforming, validating, and serving data from multiple enterprise systems.
• Build and optimize data models, data lakes, and analytics-ready datasets.
• Ensure data quality, lineage, governance, security, and compliance across all data platforms.
• Monitor and optimize data processing performance, reliability, and cost efficiency.

MLOps & Machine Learning Enablement

• Design and implement MLOps frameworks using MLFlow, Kubeflow, SageMaker, or similar platforms.
• Enable model training, experiment tracking, model registry, deployment automation, and monitoring.
• Partner with Data Scientists to operationalize machine learning models into production environments.
• Establish model versioning, reproducibility, rollback, and governance mechanisms.

Cloud & DevOps Engineering

• Create and maintain CI/CD pipelines for data engineering and machine learning workloads.
• Support containerized deployments using Docker and Kubernetes.
• Exposure to helm is a plus.
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We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.

We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace.

Work Experience

·       Bachelor's or master’s degree in computer science, Information Technology, Data Engineering, Software Engineering, or a related field.

·       5-8 years of professional experience in Data Engineering, Data Platform Engineering, or Data & AI solution development.

·       Expert-level programming skills in Python.

·       Strong SQL development and database design skills.

·       Experience building production-grade ETL/ELT pipelines and data integration solutions.

·       Experience implementing ML lifecycle management using:

• MLFlow (preferred)
• Kubeflow
• SageMaker
• Vertex AI

·       Experience building and managing CI/CD pipelines using:

• Azure DevOps
• GitHub Actions
• GitLab CI/CD
• Jenkins

·       Proficiency with Docker and Kubernetes.

·       Strong experience with Git-based source control systems.

·       Strong understanding of software design patterns, APIs, microservices, and event-driven architectures.

·       Soft Skills

o   Strong analytical and problem-solving skills.

o   Excellent wr