Roadie, a UPS company, is looking to hire a Data Engineer to build, maintain, and scale their data pipelines/platform and CI/CD processes to support a streaming architecture. The goal is to create useful, easy-to-consume data for reporting and analytics, and to help develop strategy for the long-term Data Platform architecture.
Requirements
- 4+ years of experience building data infrastructure and platforms using streaming frameworks such as Kafka/Kinesis/Flink/Spark Structured Streaming, etc.
- 4+ years of experience with PostgreSQL, as well as MPP databases such as Redshift
- 4+ years of experience with one or more language/framework such as Python/Scala/Spark/PySpark
- 4+ years of experience with scaling production systems, ideally in a start-up environment
- 3+ years of experience using CI/CD tools to build and deploy projects
- 3+ years of experience working with DevOps tools such as Docker, Kubernetes, AKS, Helm, Terraform, etc to own end-to-end deployment of Data Engineering projects
- 3+ years of experience developing and optimizing dbt models, implementing best practices, and ensuring data quality through testing and documentation. Proficient in version control (Git) and integrating dbt with modern data warehouses (e.g., Snowflake, BigQuery, Redshift, PostgreSQL).
Responsibilities
- Build efficient, high quality, integrated and increasingly real-time ETL/ELT pipelines to organize, collect, standardize and integrate data that facilitate more complete, accurate and consistent data for insights and reporting
- Partner with engineering, data science, and business stakeholders to build data insights and help them to achieve their business goals
- Deliver data capabilities and new data products to accelerate investments in data and democratize data across the enterprise
- Provide production support for data tools and data needs across the business
- Research and implement cutting edge solutions to solve challenges related to ETL/ELT, data processing, and analytics
- Participate in an on-call rotation to ensure the reliability, availability, and performance of production data pipelines and systems
Other
- Bachelor’s degree in Computer Science, Data Analytics or related field
- 5+ years of experience working with data systems, data warehouse solutions, and ETL/ELT
- 3+ years of experience working with workflow management tools such as Airflow/Luigi/Dagster
- Experience implementing data quality checks using dbt tests, custom SQL validations, and data profiling tools. Proficient in designing automated testing frameworks to ensure data accuracy, consistency, and reliability across pipelines.
- This role is not eligible for visa sponsorship. Applicants must be authorized to work for any employer in the U.S.
