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Mid-level data engineer in Bangalore with a popular title and common skillset, driving high applicant competition.
Data engineering skills are transferable across industries but require specific Databricks/dbt platform experience.
Explicit 4–6 years plus required Databricks/dbt and data-quality expertise makes shortlisting highly strict.
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Design and maintain scalable, end-to-end reconcilable data pipelines and models across multiple data layers using dbt and Databricks Delta Live Tables.
Implement and monitor data quality frameworks and SLAs to ensure data accuracy and reliability from source to final outputs, resolving upstream data issues.
Collaborate with cross-functional teams to translate business requirements into reliable data products and optimize AI-driven analytics platforms and dashboards.
4 to 6 years of experience in data engineering or closely related discipline.
Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
Hands-on experience with Databricks or equivalent AI-first data platform; proficiency in Python, SQL, dbt, and Databricks Delta Live Tables (DLT).
Experience designing data quality frameworks including schema validation, referential integrity, and real-time pipeline development.
Strong expertise in building end-to-end reconcilable data pipelines with a focus on data quality and scalability in a lakehouse architecture.
Experienced in developing AI-enabled data engineering tools, dashboards, and natural language query solutions on Databricks.
Comfortable working independently on complex data engineering challenges while collaborating across technical and non-technical teams.