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Radancy’s Data Engineering team is seeking a Senior Data Engineer to join our Bangalore Global Delivery Center 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 Radancy’s AI and analytics solutions.
Job Responsibility
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
Requirements
4-6 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
Bachelor’s or Master’s 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
Nice to have
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
Experience in AdTech, recruitment technology, HR technology, or talent acquisition data is preferred