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Tier-1 employer brand, metro Bengaluru, mid-level Data Engineer title and common cloud toolset drive high candidate competition.
Core Snowflake, Databricks, dbt and Python skills are highly transferable across industries.
Explicit 2–4 years requirement plus mandatory Snowflake/Databricks/dbt/Python skills make shortlisting moderately strict.
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Design, develop, and maintain scalable data ingestion, transformation, and ELT/ETL pipelines using SQL, Python, dbt, Snowflake, Databricks.
Build reusable dbt data models and troubleshoot issues to ensure high-quality and performant data pipelines in cloud environments.
Collaborate with engineers, architects, analysts, and business stakeholders to deliver data products that enable analytics, reporting, and business insights.
2-4 years of professional Data Engineering experience with cloud platforms like Snowflake and/or Databricks.
Proficiency in Python and SQL for data pipeline development and automation.
Bachelor’s degree in Computer Science, IT, Engineering, Data Science, Mathematics, or related field, or equivalent experience.
No visa sponsorship; work location or notice period requirements: Not explicitly mentioned in the JD.
Experienced with modern data engineering tools such as dbt, Spark, and cloud data platforms (Snowflake, Databricks, Azure/AWS/GCP).
Comfortable using AI-assisted development tools (e.g., GitHub Copilot) and automation techniques to enhance productivity and code quality.
Strong analytical and troubleshooting skills to resolve data pipeline issues, working effectively in agile and collaborative environments.