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Strong employer brand, metro location, mid-level generalist data role with broad tech requirements increases competition.
Core data engineering skills are transferable, though marketing domain experience is preferred but not mandatory.
Explicit 5+ years and mandatory Snowflake, dbt, SQL, AWS, and big-data skills enforce strict shortlisting.
Build and maintain scalable, secure data pipeline architecture and data products enabling Analytics, ML, Generative AI, and LLM applications.
Drive tool selection, data ingestion, wrangling, cataloging, and processes improving data reliability and quality from various sources including structured and unstructured data.
Collaborate with stakeholders and data scientists to support data infrastructure, resolve technical issues, and provide actionable analytics insights.
5+ years experience as Data Engineer with hands-on experience in Snowflake, dbt (including advanced concepts like macros and Jinja templating), SQL, Python, PySpark, and AWS data engineering tools (S3, EC2, Glue, Lambda, RDS, Redshift).
Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or other quantitative field.
Experience with API integrations for data exchange and optimizing big data pipelines and architectures.
Work Experience Required: 5+ years in Data Engineering. Hybrid work location in Bengaluru.
Experienced with modern data engineering practices including semantic layers, embeddings, vector search, and Retrieval-Augmented Generation (RAG) for AI applications.
Familiar with production-grade Agentic AI data services like orchestration, function calling, context management, and observability.
Preferably has Marketing domain knowledge and experience working in agile, distributed teams supporting analytic dashboards (PowerBI) and unstructured data analysis.