Cloud Data Engineer

Radial Inc.

Role Summary

We are seeking an experienced Cloud Data Engineer with strong expertise in Airflow, SQL, Snowflake, Python, and AWS. The ideal candidate will have a solid background in designing and building scalable data pipelines, cloud-based ETL solutions, and modern data warehouse platforms. This role requires strong technical skills, a problem ‑ solving mindset, and the ability to work in an Agile environment.

Responsibilities

  • Design, develop, and maintain data pipelines and workflow orchestration using Apache Airflow.
  • Build scalable and reliable ETL/ELT data pipelines using Python, SQL, and AWS data services.
  • Develop and optimize Snowflake schemas, queries, stored procedures, and data models.
  • Implement best practices in data ingestion, data transformation, and data quality validation.
  • Collaborate with cross-functional teams to gather requirements and implement end-to-end data engineering solutions.
  • Perform performance tuning, query optimization, and troubleshoot complex data issues.
  • Work across the Software Development Life Cycle (SDLC) using Agile/Scrum methodologies.
  • Ensure data security, governance, and adherence to architectural standards.

Qualifications:

  • 6+ years of professional experience in data engineering, big data, or data warehouse development.
  • Strong hands-on experience with:
    • Apache Airflow (DAG design, scheduling, monitoring).
    • Python (data processing, automation, scripting).
    • Advanced SQL (complex queries, optimization, stored procedures).
    • Snowflake (data modeling, performance tuning, Snowpipe, tasks, streams).
    • AWS services such as S3, Glue, Lambda, Athena, RDS, Redshift, IAM, etc.
    • Experience with Linux environments and shell scripting (Bash/PowerShell).
    • Strong understanding of cloud-based ETL/ELT technologies.
    • Experience working with JSON, streaming data, or Kafka/MSK.
    • Excellent knowledge of RDBMS concepts and database objects.

    Travel

    • This position is not remote.
    • Travel is not required.

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