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Mid-level, popular data engineering role in Bangalore with broad skill requirements increases competition.
Core data engineering skills are transferable across industries though AdTech/HR tech experience is preferred.
Explicit 5–8 years plus mandatory Python, SQL, Airflow, and cloud data platform experience raises filter strictness.
Design, develop, and optimize cloud-based data models, schemas, and pipelines to support analytics, AI, and insights products.
Build and maintain reliable, high-quality data pipelines integrating diverse internal and external data sources, focusing on pipeline performance, observability, and cost efficiency.
Collaborate with cross-functional teams to deliver AI-powered agentic data solutions and ensure data security, governance, and documentation adherence.
5-8 years of experience in data engineering with strong hands-on skills in SQL, Python, and data modeling.
Experience with data pipeline orchestration tools like Apache Airflow and cloud data platforms such as Google BigQuery, Amazon Redshift, Databricks, or Snowflake.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field.
Familiarity with distributed data processing (e.g., Spark, Kafka) and data quality/validation practices.
Experience building data platforms supporting AI analytics, conversational insights, or business intelligence solutions preferred.
Exposure to Generative AI tools (e.g., OpenAI, GitHub Copilot) and ability to leverage AI-assisted engineering tools to improve productivity.
Domain experience or preference for AdTech, recruitment technology, HR technology, or talent acquisition data environment.