Salary
💰 $80,000 - $120,000 per year
Tech Stack
AirflowAmazon RedshiftAWSAzureBigQueryCloudETLGoogle Cloud PlatformOraclePythonScalaSparkSQL
About the role
- As a Data Engineer at Red Ventures, you’ll build data products and create the foundation that powers our machine learning and business analytics efforts. You’ll work hand-in-hand with a variety of stakeholders from functional groups across the organization to create end-to-end solutions.
- Red Ventures is a high-autonomy, high-ownership environment; you’ll own your work from idea to production solution.
- Our data engineering tech stack is primarily AWS and Spark/SparkSQL/Python via Databricks, though we welcome strong applicants from a wide variety of technical backgrounds.
- Think of the bullets below as guidelines: if you only partially meet the qualifications on this posting, we encourage you to apply anyway!
- What You’ll Do
- Iterate – Red tape doesn’t get in our way. We believe that "Speed Trumps Perfection" so we test and deploy daily.
- Autonomy – Aspiring entrepreneurs succeed here because you will have full-ownership over your work from beginning to end.
- Innovate – With the belief that “Everything is Written in Pencil”, we encourage our teams to test new frameworks, learn new languages and challenge the “status quo” to make us better.
- Design and build data pipelines from various sources to data warehouse using batch or incremental loading strategies utilizing cutting edge cloud technologies.
- Conceptualizing and generating infrastructure that allows data to be accessed and analyzed effectively.
- Our Data Engineers within the Home vertical play a pivotal role in constructing the data processing pipelines that drive our proprietary brands and our key partnerships. As a member of this team, you will contribute to the development of a Homogenized Multi-Tenant Data Warehouse. Your primary responsibility will involve hands-on tasks to transform existing data from diverse enterprise systems into a unified data platform housing robust datasets ready for analytics and reporting. This entails mastering upstream processes, pipelines, and source systems. Moreover, you will collaborate with various functional units to ensure the successful deployment, operation, and maintenance of solutions.
- What We’re Looking For
- 2+ years of experience performing production data engineering/ETL work
- 2+ years of experience with one of the major cloud providers (we use AWS but we welcome candidates with experience in Azure or GCP)
- 2+ years of experience working on Spark/SparkSQL using Scala/Python to build and maintain complex ETL pipelines
- 2+ years of experience working with SQL
- Experience with GitHub and CI/CD processes
- Experience working on Orchestration (Databricks Workflows / Airflow)
- Experience with one of the major data warehousing solutions (we use Databricks but we welcome candidates with experience in BigQuery, Snowflake, Oracle or Redshift)
- Conceptual understanding of data warehousing and dimensional modeling
- Experience providing operational support for the production data pipelines and data triaging
- Familiarity with SaaS like Fivetran and Hightouch is a plus
Requirements
- 2+ years of experience performing production data engineering/ETL work
- 2+ years of experience with one of the major cloud providers (AWS, Azure, or GCP)
- 2+ years of experience working on Spark/SparkSQL using Scala/Python to build and maintain complex ETL pipelines
- 2+ years of experience working with SQL
- Experience with GitHub and CI/CD processes
- Experience working on Orchestration (Databricks Workflows / Airflow)
- Experience with one of the major data warehousing solutions (we use Databricks but we welcome candidates with experience in BigQuery, Snowflake, Oracle or Redshift)
- Conceptual understanding of data warehousing and dimensional modeling
- Experience providing operational support for the production data pipelines and data triaging
- Familiarity with SaaS like Fivetran and Hightouch is a plus