Senior Data engineer

Key Responsibilities

1. Platform & Application Architecture

• Architect and oversee end-to-end platform design using GCP services (Vertex AI, Cloud Run, GKE, Pub/Sub, Firestore, BigQuery, and IAM).
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• Define the architecture for multi-tenant SaaS deployment—ensuring secure data boundaries across customers while maintaining a single codebase.
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• Collaborate closely with backend developers to optimize Node.js APIs, data pipelines, and event-driven microservices.
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• Design front-end integration flows and ensure UI/UX alignment with backend AI and agentic processes.
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2. AI / LLM / Agentic System Architecture

• Lead architecture for all AI initiatives involving RAG pipelines, AI agents, NLP, and conversational AI.
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• Evaluate and integrate LLMs and APIs from OpenAI, Google Gemini, Anthropic (Claude), Mistral, and others.
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• Define frameworks for AI agent orchestration, prompt engineering, and function/tool calling workflows using frameworks like LangChain or LlamaIndex.
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• Establish standards for vector databases (Pinecone, FAISS, Chroma), embeddings, chunking strategies, and retrieval optimization.
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• Architect an AgentOps layer for monitoring, safety filtering, and AI model governance.
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3. MLOps, PromptOps & DevOps Integration

• Implement CI/CD pipelines for AI models, prompts, and agents using Cloud Build, Terraform, and GitHub Actions.
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• Design PromptOps and MLOps pipelines to manage model lifecycle, versioning, rollback, and production promotion.
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• Define observability and monitoring mechanisms (OpenTelemetry, Cloud Monitoring, custom logs for LLM outputs).
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• Collaborate with DevOps engineers to define blue/green and canary deployments across environments.
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4. Security, Compliance & Scalability

• Design tenant-isolated data layers using IAM, VPC-SC, and KMS encryption policies to meet regulatory standards (HIPAA, GxP, GDPR).
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• Implement data governance, access control, and threat detection mechanisms for AI-driven workflows.
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• Create performance optimization strategies: GPU/TPU allocation, autoscaling policies, token budgets, response caching, and FinOps visibility.
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5. Cross-Functional Leadership

• Partner with Product Managers and Business Analysts to translate business requirements into architectural blueprints.
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• Work with UX/UI designers to ensure front-end experiences align with AI agent capabilities and backend APIs.
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• Provide architectural guidance and technical mentorship to developers, ensuring adherence to best practices across projects.
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• Contribute to platform evolution, reference architecture libraries, and reusable design patterns.
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Key Skills & Qualifications

Technical Expertise

• Strong background in cloud architecture, specifically Google Cloud Platform (GCP)—Vertex AI, Cloud Run, Cloud Storage, IAM, Pub/Sub, BigQuery, VPC, and Cloud Functions.
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• Proficiency with Node.js, TypeScript, and API development for scalable microservices.
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• Deep understanding of LLMs, AI agent frameworks, retrieval-augmented generation (RAG), and vector search.
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• Experience with LangChain, LlamaIndex, CrewAI, and Agentic AI design patterns.
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• Strong understanding of data architecture, including NoSQL/SQL databases (MongoDB, Firestore, PostgreSQL).
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• Hands-on experience with container orchestration (Docker, Kubernetes) and Infrastructure-as-Code (Terraform).
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Preferred Skills

• Prior experience designing multi-tenant SaaS platforms.
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• Exposure to frontend integration (Angular, React, or similar) and UI/UX flow understanding.
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• Knowledge of AI safety, risk frameworks, and prompt governance.
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• Strong analytical and communication skills for working across business and technical stakeholders.
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• Awareness of FinOps and cost optimization in token-based AI ecosystems.
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Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, or Cloud Architecture.
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• 8–12 years of professional experience, with at least 3 years focused on AI platform architecture or enterprise-grade SaaS system design.
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Certifications in GCP Professional Cloud Architect or Machine Learning Engineer are a plus.

We are seeking a talented Front-End Developer based in India to work with us on an ongoing freelance or contract basis. As a key member of our team, you’ll handle a variety of tasks, including resolving technical issues, implementing site updates, customising Shopify themes, optimising user experiences, and ensuring seamless site performance.

The ideal candidate has expertise in HTML, CSS, JavaScript (React.js, Vue.js, or similar), and Shopify theme development, with a strong understanding of responsive design, debugging, and cross-browser compatibility.

Also has experience with SEO, Shopify Plus, or basic back-end development.

Role: Head of Analytics

Location: Bangalore (Full time)

ABOUT QRATA: 

Qrata matches top talent with global career opportunities from the world’s leading digital companies including some of the world’s fastest growing startups using Qrata’s talent marketplaces. To sign-up, please visit Qrata Talent Sign-Up 

ABOUT THE COMPANY WE ARE HIRING FOR: 

Our client is offering credit card solutions for banks and financial institutions. It provides services like credit card design and onboarding, credit card authorization, payment processing, collections and dispute resolutions, credit card fraud detection, and more. They serve in the B2B space in the FinTech market segments.

POSITION OVERVIEW 

We are seeking an experienced individual for the role of Head of Analytics. As the Head of Analytics, you will be responsible for driving data-driven decision-making, implementing advanced analytics strategies, and providing valuable insights to optimize our credit card business operations, sales and marketing, risk management & customer experience. Your expertise in statistical analysis, predictive modeling, and data visualization will be instrumental in driving growth and enhancing the overall performance of our credit card business.

Responsibilities:

1. Develop and implement Analytics Strategy:

o Define the analytics roadmap for the credit card business, aligning it with overall

business objectives.

o Identify key performance indicators (KPIs) and metrics to track the performance

of the credit card business.

o Collaborate with senior management and cross-functional teams to prioritize and

execute analytics initiatives. 2. Lead Data Analysis and Insights:

o Conduct in-depth analysis of credit card data, customer behavior, and market trends to identify opportunities for business growth and risk mitigation.

o Develop predictive models and algorithms to assess credit risk, customer segmentation, acquisition, retention, and upsell opportunities.

o Generate actionable insights and recommendations based on data analysis to optimize credit card product offerings, pricing, and marketing strategies.

o Regularly present findings and recommendations to senior leadership, using data visualization techniques to effectively communicate complex information.

3. Drive Data Governance and Quality:

o Oversee data governance initiatives, ensuring data accuracy, consistency, and

integrity across relevant systems and platforms.

o Collaborate with IT teams to optimize data collection, integration, and storage

processes to support advanced analytics capabilities.

o Establish and enforce data privacy and security protocols to comply with

regulatory requirements.

4. Team Leadership and Collaboration:

o Build and manage a high-performing analytics team, fostering a culture of innovation, collaboration, and continuous learning.

o Provide guidance and mentorship to the team, promoting professional growth and development.

o Collaborate with stakeholders across departments, including Marketing, Risk Management, and Finance, to align analytics initiatives with business objectives.

5. Stay Updated on Industry Trends:

o Keep abreast of emerging trends, techniques, and technologies in analytics, credit

card business, and the financial industry.

o Leverage industry best practices to drive innovation and continuous improvement

in analytics methodologies and tools.

Qualifications:

Bachelor's or master’s degree in Technology, Mathematics, Statistics, Economics, Computer Science, or a related field.

Proven experience (7+ years) in leading analytics teams in the credit card industry.

Strong expertise in statistical analysis, predictive modelling, data mining, and segmentation techniques.

Proficiency in data manipulation and analysis using programming languages such as Python, R, or SQL.

Experience with analytics tools such as SAS, SPSS, or Tableau.

Excellent leadership and team management skills, with a track record of building and developing high-performing teams.

Strong knowledge of credit card business and understanding of credit card industry dynamics, including risk management, marketing, and customer lifecycle.

Exceptional communication and presentation skills, with the ability to effectively communicate complex information to a varied audience. 

• Handling end to end Technical Recruitment across various verticals.
• Stakeholder management, client and talent management
• Using Job portals like Naukri, CutShort, Angel List, Linkedin Recruiter, Hyrst, Instahyre, etc for recruitment.
• Preferred candidate:- BE / Btech / BCA / MCA / Mtech / MS or someone from a technical background

Zycus is looking for applicants with a strong background in Analytics and Data mining (Web, Social and Big data), Machine Learning, Pattern Recognition, Natural Language Processing, Computational Linguistics, Statistical Modelling, Inferencing, Information Retrieval, Large Scale Distributed Systems, Cloud Computing, Econometrics, Quantitative Marketing, Applied Game Theory, Mechanism Design, Operations Research, Optimization, Human Computer Interaction and Information Visualization. Applicants with a background in other quantitative areas are also encouraged to apply.

We are looking for someone who can create and implement AI solutions. If you have built a product like IBM WATSON in the past and not just used WATSON to build applications, this could be the perfect role for you.

All successful candidates are expected to dive deep into problem areas of Zycus’ interest and invent technology solutions to not only advance the current products, but also to generate new product options that can strategically advantage the organization.

Roles & Responsibilities:

• Act as a technical thought leader in collaboration with the analytics leadership team, helping to set the strategy and standards for Machine Learning and advanced analytics
• Work with senior leaders from all functions to explore opportunities for using advance analytics
• Provide technical leadership, coaching, and mentoring to talented data scientists and analytics professionals
• Guide data scientists in the use of advanced statistical, machine learning, and artificial intelligence methodologies
• Guide the work of other Machine learning team members to provide support and assistance, while also ensuring quality