Description
We are looking for a highly skilled Data Engineer (Cloud, AI & Analytics) with strong hands-on experience across cloud data engineering, advanced analytics, and artificial intelligence.
This role requires deep technical expertise in architecting scalable data pipelines, building enterprise data models, and designing production-grade AI systems-including LLMs and generative AI-to drive business insight and automation.
Key Responsibilities
- Architect, design, and maintain scalable, resilient data pipelines and enterprise data models to support analytics, AI, and business intelligence use cases.
- Design, build, and optimize ETL/ELT frameworks using Azure Data Factory (ADF) and cloud-native data integration patterns.
- Develop and manage cloud data platforms using Snowflake for high-performance, cost-efficient analytics workloads.
- Design and implement advanced AI and machine learning systems, including deep learning, NLP, large language models (LLMs), and generative AI solutions.
- Lead AI research, experimentation, and prototyping to solve complex business problems and identify automation opportunities.
- Build and operationalize end-to-end ML pipelines, from data preparation and feature engineering to deployment and monitoring.
- Develop executive dashboards and analytical applications that deliver actionable insights and support strategic decision-making.
- Implement CI/CD pipelines to automate data and AI workflows, ensuring reliability, reproducibility, and faster releases.
- Collaborate with engineering, analytics, product, and business teams to ensure seamless system integration and alignment with business objectives.
- Establish data engineering, analytics, and AI best practices, including governance, quality, security, and observability.
- Stay current with emerging data, AI, and LLM technologies to drive continuous innovation.
Required Skills
- Strong proficiency in Python for data engineering, analytics, and machine learning development.
- Hands-on experience with Snowflake for cloud data warehousing and analytics.
- Experience designing and implementing data pipelines using Azure Data Factory (ADF) or equivalent ETL/ELT tools.
- Solid experience with AI/ML techniques, including deep learning, NLP, and LLMs / generative AI.
- Experience building analytical models, experiments, and AI-driven solutions for real-world business problems.
- Strong understanding of enterprise data modeling, data quality, and scalable pipeline design.
- Experience implementing CI/CD pipelines for data and ML workflows using modern DevOps practices.
- Experience building dashboards and analytical applications using modern BI or visualization tools(Tableau/Power BI).
- Familiarity with cloud platforms (Azure preferred; AWS/GCP acceptable).
- Strong communication skills to translate complex technical concepts into business insights.
Preferred / Nice-to-Have Skills
- Experience with MLOps practices, model deployment, monitoring, and observability.
- Experience with telecom network data (5G, LTE, VoLTE, SMS, data usage, roaming).
- Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) patterns.
- Experience integrating LLMs with enterprise data and applications.
- Experience working in Agile teams and large-scale enterprise environments.
- Should have background in Telecom industry.
(ref:hirist.tech)
