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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

3–5 yearsUNKNOWNofficeDirect Career PageEst. 9–16 LPA

Posted 7h 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)

Mid-level, common Data Engineer title with 3-5 years band and moderate company brand.

Background Fit Sensitivity

(Low)

Core data engineering and cloud skills are broadly transferable across industries.

Shortlisting Strictness

(High)

Explicit 3-5 years plus mandatory AWS, Snowflake, Python, SQL, and vector/graph DB experience.

Structured overview of role & requirements

Design, develop, and maintain scalable data pipelines using AWS services including S3, Glue, Lambda, Redshift, and EMR.

Build and optimize Snowflake data warehousing solutions, including performance tuning and data modeling.

Integrate vector and graph databases into LLM-based AI applications and collaborate with cross-functional teams to meet data requirements.

3-5 years of experience in data engineering or related roles.

Strong hands-on experience with AWS cloud services and Snowflake architecture.

Advanced proficiency in Python and SQL.

Experience with graph databases (e.g., Neo4j, Neptune) and vector databases (e.g., Milvus, Amazon OpenSearch).

Experienced in building and optimizing large-scale AWS cloud data pipelines with a focus on reliability and performance.

Skilled in integrating advanced database technologies such as graph and vector databases within AI/ML workflows.

Familiar with Agile development environments using Azure DevOps and version control with Git.