3 months ago
Remote, United StatesSenior
Responsibilities
- Design and build scalable data pipelines using GCP services including Cloud Dataflow, Cloud Pub/Sub, Data Stream, Spark, and Cloud Composer.
- Develop, test, and maintain data models, schemas, and ETL processes using BigQuery, Cloud SQL, Spark, and Data Studio.
- Translate stakeholder requirements into effective data infrastructure solutions.
- Optimize pipelines for performance, scalability, and cost efficiency using GCP-native tools such as Dataproc and Bigtable.
- Build validation processes and enforce data quality, governance, access control, and security practices.
- Automate reliable, scheduled workflows with Cloud Composer.
- Own data pipeline and infrastructure reliability, including monitoring, alerting, troubleshooting, and root cause analysis.
- Partner with SRE and Infrastructure teams on shared GCP compute, storage, and network resources.
- Prepare, model, and expose governed data for ML and agentic AI use cases.
- Mentor the broader data team on pipeline design and data infrastructure standards.
- Monitor GCP’s roadmap and apply emerging data engineering best practices to the platform.
Requirements
- 5+ years of data engineering experience, including at least 3 years in a cloud environment, preferably GCP.
- Expertise with GCP services including BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud Storage, Cloud Functions, and Cloud SQL.
- Strong SQL skills with experience writing complex data extraction and analysis queries.
- Hands-on ETL development and workflow orchestration experience using tools such as Apache Airflow.
- Proficiency in Python and/or Spark for data processing and pipeline development.
- Experience with both streaming data pipelines and batch processing.
- Understanding of data warehousing, large datasets, and query optimization.
- Working knowledge of data governance, cloud security, and compliance.
- Understanding of ML concepts and data preparation for ML applications, with interest in agentic AI tooling.
- Strong analytical, problem-solving, troubleshooting, communication, and collaboration skills.
- Bachelor’s degree in computer science or a comparable field, or equivalent experience.
- Preferred GCP certification such as Professional Data Engineer or Cloud Architect.
- Preferred experience with GCP ML infrastructure such as AI Platform and TensorFlow.
- Preferred familiarity with DevOps/MLOps practices, infrastructure as code, and containerization on GCP.
- Preferred experience with Apache Spark and backgrounds in logistics, supply chain, 3PL, or warehouse and fulfillment technology.
- Experience working on a distributed team is preferred.
Tech Stack
Apache AirflowApache SparkDockerGoogle BigQueryGoogle Cloud PlatformKubernetesPythonSQLTensorFlowTerraform
Categories
Data Engineering
About Stord
Stord provides a commerce enablement platform that combines third-party warehousing and transportation with OMS, WMS, and post‑purchase software for brands selling online and omnichannel. Its business model blends 3PL fulfillment and freight services with SaaS subscriptions. Founded in 2015 and headquartered in Atlanta, it operates a fulfillment network across the U.S., Canada, and Europe, and serves brands such as AG1, Native, and quip.