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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, mid-level Data Engineer role, metro location, and broad in-demand cloud and Snowflake/Databricks skills.
Specialized data engineering and cloud tooling required, so cross-industry transferability is moderate.
Explicit 5–7 years plus mandatory cloud, Snowflake/Databricks, Spark, SQL, and CI/CD requirements.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and manage scalable data pipelines and advanced data structures ensuring data quality and accessibility across cloud platforms such as Snowflake and Databricks.
Develop and optimize SQL-based transformations and ingestion frameworks to deliver reliable and high-quality data for analytics, reporting, and downstream applications.
Collaborate with cross-functional teams, mentor junior engineers, and improve internal data engineering tools and automation to enhance operational efficiency and scalability.
Minimum Requirements
4-7 years of experience in Data Engineering.
Proficiency in advanced SQL and Python or similar programming languages.
Experience with at least one cloud platform (AWS, GCP, or Azure), Snowflake or Databricks, and exposure to distributed computing frameworks such as Apache Spark.
Bachelor's degree preferred; relevant combinations of coursework and experience may be considered.
Ideal Candidate Profile
Strong hands-on experience in cloud-based data engineering with platforms like Snowflake, Databricks, and cloud storage technologies such as AWS S3.
Capable of working independently in complex technical environments while contributing to team standards and mentoring junior engineers.
Experience implementing CI/CD, workflow orchestration (e.g., Airflow/dbt), and improving data governance and lineage for dependable business insights.