Marketing Data Engineer

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Company: Codeforce360

Location: Seattle, WA 98115

Description:

Required Skills:

Position Summary:

The Marketing Data Engineer contractor contributes technical solutions on behalf of the company's Marketing Data Engineering team.
This team is responsible for building and operating our cloud-based Marketing data platform that enables self-service analytics.
The Marketing Data Engineer role will develop and help solve challenging data integration problems by participating in development and operations work related to building the Marketing Data Platform.
The role will collaborate with other Data Engineers, Data Scientists, Analysts as well as our internal marketing customers to scope and define implementation plans that meet business requirements.

Project Scope:

The Marketing team is currently migrating it's legacy data architecture along with its pipelining and ETL processes over to AWS in a system that utilizes Airflow, custom Python modules, and dbt for data modeling.
The Marketing Data Engineer will be responsible for building custom data pipelines from multiple data sources (API sources, flat files, etc.) within this new data architecture.

Primary Responsibilities (Essential Functions):

Build robust scalable data processing and data integration pipelines using Python and SQL.
Develop data quality automations and unit tests to ensure the accuracy of the data delivered to the Analysts and Business Customers.
Build solutions that scale as our data volumes grow exponentially.
Define and implement monitoring and alerting policies for data solutions.
Develop data models that support analytical models used by the company.
Test and document data pipelines that are developed.
Regular, predictable job attendance.

Knowledge and Skill Requirements:

Demonstrated experience writing Python code.
Good understanding of RESTful APIs, data streaming, and other data sourcing technologies.
Demonstrated experience writing optimized SQL queries across large data sets.
Experience with Git.
Experience with Snowflake.
Experience with Airflow.
Experience with containers and container orchestration tools such as Docker and Kubernetes.
Experience with CI/CD pipelines and the SDLC.
AWS Certifications on either a Developer or Architect is preferred but not required.

Experience:

BA/BS in Computer Science or equivalent.
4+ year's professional experience in Data Engineering role.
A technical background in ETL development and data warehousing concepts is preferred.
Proven technical leadership and mentoring of other engineers.