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Protocol Intelligence

Data-driven signals on your job's competitiveness

CV Match Score

Estimated fit based on your resume

Structured overview of role & requirements

tenPlusofficeDirect Career PageEst. 20–35 LPA

Posted 21h ago

Against your primary resume

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Role Fit

Experience

Industry Relevance

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Data-driven signals on your job's competitiveness

Competition Intensity

(Moderate)

Medium — senior-level role with in-demand Azure/Databricks skills but at a non-Tier-1 employer.

Background Fit Sensitivity

(Moderate)

Medium — data engineering skills transferable across industries but tool-specific Azure/Snowflake experience increases specificity.

Shortlisting Strictness

(High)

High — explicit 10+ years and specific Azure Databricks, Snowflake, PySpark, and ETL experience required.

Structured overview of role & requirements

Design, develop, and optimize scalable data pipelines and data warehouses on Azure Databricks, Azure Data Factory, and Snowflake.

Migrate data from multiple sources to Databricks and implement data quality and governance frameworks.

Support business intelligence and KPI reporting by collaborating with stakeholders and managing Agile delivery processes.

10+ years of data engineering experience.

Strong expertise in Azure Databricks, Azure Data Factory, Snowflake, Python, PySpark, SQL, data modeling, and ETL development.

Experience with data governance and Agile methodologies.

Work Experience Required: 10+ years.

Experienced in managing end-to-end data engineering projects in cloud environments, especially Azure.

Proficient in stakeholder management and Agile delivery processes, indicating ability to work cross-functionally.

Strong technical background with hands-on skills in advanced data engineering tools and frameworks including Snowflake and Databricks.