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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

5–8 yearsUNKNOWNofficeDirect Career PageEst. 12–20 LPA

Posted 21h ago

Against your primary resume

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Data-driven signals on your job's competitiveness

Competition Intensity

(Moderate)

Mid-level data engineer with common skills and Databricks specialization draws moderate competition.

Background Fit Sensitivity

(Low)

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

Shortlisting Strictness

(High)

Explicit 5-8 years plus mandatory Databricks, Spark, cloud, Python and SQL indicate high shortlisting strictness.

Structured overview of role & requirements

Build and maintain data engineering pipelines using Databricks, Apache Spark, and cloud services (AWS or Azure).

Develop data transformation workflows and manage data modeling following dimensional modeling concepts.

Implement version control and CI/CD practices for data solutions, supporting data governance and security requirements.

5-8 years of data engineering experience.

Proficient in Python, SQL, and Apache Spark (PySpark preferred).

Experience with Databricks including Delta Lake and Databricks Workflows.

Hands-on experience with cloud data services on AWS (S3, Glue, EMR) or Azure (ADLS Gen2, Data Factory, Synapse).

Experienced with Databricks Certified Data Engineer Associate certification or pursuing it.

Knowledgeable in streaming data pipelines using Structured Streaming, Kafka, Kinesis, or Event Hubs.

Familiar with orchestration tools like Airflow or Databricks Workflows and basic data governance/security practices.