Data Engineer III
About The Position
Lead the design, development, and maintenance of ETL processes using Snowflake and AWS Cloud Services. Extract structured and semi-structured commercial datasets from upstream Oracle source systems into Snowflake cloud data warehouses, and use Fivetran to support data extraction, transformation, and loading. Improve business data pipelines for efficiency, performance, and scalability. Use BigQuery to perform complex data transformations for marketing teams and create dashboards in Looker. Use custom frameworks, including SFTP and APIs, to handle CSV, JSON, and relational database data. Manage codebase integrity, version control pipelines, and software deployment using GitHub. Develop a framework to streamline transformations across structured and unstructured formats and support automated scheduling and monitoring. Write and troubleshoot advanced SQL and Python code, implement automated data quality checks and validation, and work with commercial product managers to ensure accurate and reliable data delivery. Document ETL processes, data models, and framework functionality, and stay current with data engineering technologies and trends.
Requirements
- Master’s degree in Computer Science.
- At least 2 years of experience in the job offered.
- Proficiency with ETL and Fivetran or Matillion.
- Proficiency with Snowflake and complex Oracle data transformations.
- Proficiency with JSON, CSV, APIs, and SFTP.
- Proficiency with SQL and Python.
- Proficiency with AWS Cloud Services.
- Proficiency with GitHub administration.
- Proficiency with Agile/Scrum SDLC.
Responsibilities
- Lead the design, development, and maintenance of ETL processes using Snowflake and AWS Cloud Services.
- Extract structured and semi-structured commercial datasets from Oracle source systems into Snowflake data warehouses.
- Use Fivetran for data extraction, transformation, and loading.
- Improve data pipelines for efficiency, performance, and scalability.
- Use BigQuery to perform complex transformations for marketing teams and create dashboards with Looker.
- Use SFTP, APIs, and custom frameworks to handle CSV, JSON, and relational database data.
- Manage codebase integrity, version control pipelines, and software deployment using GitHub.
- Develop a framework for transforming structured and unstructured data formats and supporting automated scheduling and monitoring.
- Generate and troubleshoot SQL and Python code.
- Implement automated data quality checks and validation processes.
- Work with commercial product managers to ensure accurate and reliable data delivery.
- Document ETL processes, data models, and framework functionality.
- Stay updated on emerging data engineering technologies and trends.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
