Overview

Are you a hands-on engineer who enjoys solving complex problems across cloud, data and AI

Responsibilities

• Design, build and operate production-grade software and data solutions end-to-end—from problem definition and architecture through implementation, 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.
• Model, curate and optimise Snowflake datasets, schemas and data structures, ensuring performance, quality, consistency and usability.
• Apply strong software engineering practices including clean code, modular design, automated testing, CI/CD, observability, secure development and maintainable architecture.
• Partner with business and technical stakeholders to translate requirements into robust data solutions and identify opportunities for advanced analytics and AI use cases.
• Use AI-assisted engineering tools as part of everyday development to accelerate coding, refactoring, documentation, testing, debugging and solution exploration.
• Build cloud-native integrations and automation on AWS, including compute, storage, networking, security, orchestration, event-driven architectures and managed AI services.
• Own deployment, release and production operations, including troubleshooting, root-cause analysis, performance tuning, incident resolution, peer reviews and engineering best practices.

Qualifications

• 7+ years of professional experience in hands-on software engineering, solution engineering or data engineering roles.
• Deep hands-on experience with AWS, including compute, storage, networking, IAM, security, orchestration, monitoring and serverless/event-driven architectures.
• Deep hands-on Snowflake experience, including data modelling, SQL performance tuning, pipeline integration, access control, cost/performance optimisation, data sharing and platform governance.
• Strong proficiency in Python and/or Java, with a solid understanding of software design principles, APIs, automated testing, packaging, dependency management and production maintainability.
• Amazon Bedrock and other AWS AI services
• Agent-based AI solution patterns
• Retrieval-Augmented Generation (RAG)
• Model evaluation, guardrails and responsible AI
• GitHub Copilot, Claude, Cursor or similar AI-assisted engineering tools
• Harness engineering or similar AI-assisted development concepts
• AWS or Snowflake certifications
• Experience working with sensitive or regulated enterprise data
• Financial-services industry experience
• Strong familiarity with Git, CI/CD, DevOps, infrastructure-as-code, automated testing and production support.
• Strong collaboration and communication skills, with the ability to work closely with business stakeholders and cross-functional technology teams.
• Notice Period: Immediate to 60 days
• Compensation: Approximately 30–36 LPA, depending on experience and current CTC
• If you're looking for an opportunity where software engineering, cloud, data and AI come together, we'd love to hear from you.
• Interested DM us or share your CV along with your current CTC, expected CTC, notice period and current location.
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