Data Engineer (Snowflake / Databricks / BigQuery)
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Protocol Intelligence
Data-driven signals on your job's competitivenessRemote role, popular Data Engineer title, mid-level range increases competition despite niche mandatory certifications.
Core data engineering skills are transferable, but mandatory platform certifications and cloud-specific tooling raise fit sensitivity.
Mandatory platform certifications, specific cloud toolset, and explicit years make shortlisting highly strict.
Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and optimize scalable data ingestion pipelines and ELT/ETL transformation models for structured, semi-structured, and unstructured enterprise data.
Architect and manage enterprise cloud data platforms (Snowflake, Databricks, BigQuery), optimizing schemas, query performance, and cost-efficiency.
Implement automated data orchestration workflows and enforce strict data quality, validation, and compliance controls including security and access governance.
Minimum Requirements
4 to 8 years of database engineering or backend development experience; minimum 3 years dedicated data engineering on enterprise-scale infrastructure.
Mandatory certification: Snowflake Core Data Engineer, Databricks Data Engineer Professional, or Google Cloud Professional Data Engineer.
Strong expertise in SQL optimization, Python, relational/dimensional data modeling, and cloud storage systems.
Experience with distributed computing, big data architectures, and cloud resource management pricing.
Ideal Candidate Profile
Experienced in building and maintaining enterprise-grade cloud data platforms using Snowflake, Databricks, or BigQuery.
Proficient in designing scalable, performant ELT/ETL pipelines and automating data workflows with tools like Apache Airflow or Prefect.
Skilled in data governance including security, compliance, and cost optimization of cloud data environments.