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Protocol Intelligence
Data-driven signals on your job's competitivenessRemote role, popular generalist title, and broad skillset requirements increase candidate competition.
Core data engineering skills (Python, SQL, ETL, Kafka, Snowflake) transfer easily across industries.
Explicit 2+ years plus mandatory cloud, pipeline, and messaging stack creates stringent filtering.
Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and maintain scalable and secure data pipelines using modern data platforms like Spark, Databricks, Airflow, and Snowflake.
Develop ETL/ELT processes for ingesting structured and unstructured data sources and perform exploratory data analysis to support data product development and business decisions.
Collaborate with data scientists, analysts, and engineers in designing data models and ensure reliability by writing clean, tested Python code with ownership of end-to-end feature delivery.
Minimum Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Minimum 2 years of experience in data engineering or backend software development.
Proficiency in Python, SQL, relational databases (RDS, MySQL, PostgreSQL), and experience with data pipeline orchestration tools (e.g., Apache Airflow).
Experience with cloud data platforms such as AWS Redshift, GCP BigQuery, Snowflake, or Databricks; familiarity with Apache Kafka or RabbitMQ for asynchronous systems.
Ideal Candidate Profile
Experienced in distributed systems, data modeling, and data warehousing with ability to build scalable data infrastructure.
Comfortable working in agile, collaborative environments integrating with data science and software engineering teams.
Experience or interest in DevOps practices (CI/CD, containerization), data security/privacy regulations, and exposure to AI/ML data solutions or large language model integrations.