Senior Data Engineer - Generative AI

About the Role : Radancys Data Engineering team is seeking a Senior Data Engineer to join our Bangalore Product Engineering team and help build the next generation of our data platform, insights products, and AI-powered data agents. This role is part of our evolution from serving traditional data engineering needs to building intelligent, customer-facing data products that power insights agents, data agents, predictive analytics, and AI-driven decision support. You will work on data acquisition, data modeling, pipeline development, cloud-native data platforms, and agentic solutions that help employers better understand and act on their recruitment data. Your work will be foundational to delivering high-quality, reliable, and well-governed data for Radancys AI and analytics solutions. What does a great Senior Data Engineer do ? - Design, develop, and optimize data models, schemas, and datasets for cloud-based data platforms. - Build, optimize, and maintain reliable data pipelines using Python, SQL, Airflow, and cloud data technologies. - Ingest, transform, aggregate, and curate data from diverse internal and external sources to create high-quality datasets for analytics, reporting, AI, and agentic solutions. - Work with domain experts, product teams, analytics teams, and engineering stakeholders to understand business needs and translate them into scalable data solutions. - Support the development of Insights Agents and Data Agents that help users ask questions, generate insights, summarize trends, and make data-driven decisions. - Develop AI-assisted and agentic solutions that generate actionable insights, business narratives, and compelling data stories from structured and semi-structured data. - Use agentic software development tools and Generative AI tools to improve engineering productivity, including code generation, test creation, documentation, data validation, troubleshooting, and workflow automation. - Continuously improve pipeline performance, reliability, observability, and cost efficiency through optimization, automation, and proactive monitoring. - Build and maintain data quality frameworks, automated tests, validation checks, and monitoring processes to ensure trustworthy data. - Collaborate with global engineering teams to define standards for data collection, modeling, governance, and AI-readiness. - Assist with technical documentation for data models, pipelines, workflows, data contracts, and agentic data solutions. - Ensure data security, platform security, data governance, and AI governance practices are followed to support compliant and ethical use of data. Qualifications : - 5 to 8 years of experience in data engineering, including strong hands-on experience with SQL, Python, and data modeling. - Experience building and optimizing data pipelines using Apache Airflow or similar orchestration tools. - Strong experience with cloud data platforms such as Google BigQuery, Amazon Redshift, Databricks, Snowflake, or similar technologies. - Experience working with large-scale structured and semi-structured datasets. - Familiarity with distributed data processing technologies such as Spark, Kafka, or similar frameworks. - Experience with data quality, data validation, pipeline monitoring, and automated testing practices. - Exposure to Generative AI tools such as OpenAI, Gemini, GitHub Copilot, Cursor, or similar tools is strongly preferred. - Ability to use AI-assisted or agentic development tools to improve productivity, troubleshoot issues, generate tests, and accelerate delivery. - Experience with Machine Learning, MLOps, predictive analytics, or AI-powered analytics is a plus. - Experience building datasets or platforms that support analytics products, conversational insights, data agents, or business intelligence solutions is a plus. - Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related field. - Experience in AdTech, recruitment technology, HR technology, or talent acquisition data is preferred. - Strong problem-solving skills, attention to detail, communication skills, and eagerness to learn new business domains and technologies.