Senior Data Engineer (AWS & Snowflake)

We are looking for a hands-on Senior Data Engineer who can design, build, and operate robust cloud-native data and AI solutions. The ideal candidate combines strong software engineering fundamentals with deep practical experience in AWS and Snowflake.

You Will Have The Following Responsibilities

• Design, build, and operate production-grade data solutions end-to-end, from architecture and implementation through deployment, monitoring, and continuous improvement.
• Design and implement reliable, scalable, secure, and well-governed data pipelines and data products using AWS and Snowflake across structured, semi-structured, and unstructured data sources.
• Model, curate, and optimize Snowflake datasets, schemas, and data structures to ensure performance, data quality, consistency, governance, and usability.
• Apply software engineering best practices including clean code, modular design, automated testing, CI/CD, observability, secure development, and maintainable architecture.
• Partner with business and technical stakeholders to translate business requirements into scalable data engineering solutions and identify opportunities for analytics and AI initiatives.
• Build cloud-native integrations and automation using AWS services including compute, storage, networking, security, orchestration, and serverless technologies.
• Utilize AI-assisted engineering tools to improve coding, testing, documentation, debugging, and overall engineering productivity while maintaining high-quality standards.
• Own deployment, release management, production support, troubleshooting, root cause analysis, performance tuning, and incident resolution.
• Participate in peer code reviews, pair programming, and continuous improvement of engineering standards and practices.

You Will Have The Following Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Information Technology, Data Science, Artificial Intelligence, or a related technical discipline.
• At least 7 years of hands-on experience in Data Engineering, Software Engineering, or Cloud Engineering, with a proven track record of delivering enterprise-grade data solutions.
• Demonstrated experience building and supporting cloud-native data platforms, data pipelines, and data products in production environments.
• Strong hands-on experience with AWS, including compute, storage, networking, IAM, security, orchestration, monitoring, and serverless or event-driven services.
• Strong hands-on experience with Snowflake, including data modeling, SQL performance tuning, data pipeline integration, access control, cost optimization, data sharing, and platform governance.
• Strong proficiency in Python and/or Java, with solid knowledge of software design principles, APIs, automated testing, dependency management, and application maintainability.
• Experience with AWS AI services such as Amazon Bedrock, and familiarity with Generative AI, Retrieval-Augmented Generation (RAG), AI agents, and responsible AI practices is an advantage.
• Experience using AI-assisted engineering tools such as GitHub Copilot, Claude, Cursor, or similar as part of daily development.
• Strong understanding of Git-based workflows, CI/CD, Infrastructure as Code (IaC), DevOps practices, automated testing, and production support.
• Ability to translate business requirements into technical solutions and deliver scalable, maintainable data platforms.
• Strong analytical, problem-solving, communication, and stakeholder management skills.
• Experience working with sensitive and confidential data while implementing governance, security, and compliance controls.
• AWS certifications (Solutions Architect, Data Engineer, or Machine Learning Engineer Associate) and SnowPro certifications are preferred.
• Experience in the financial services industry is an advantage.