
201 - 500 employees
Founded 1993
📦 Logistics
💼 Consulting
☁️ SaaS
💰 Corporate Round on 2017-10
Logistics • Consulting • SaaS
Baxter Planning is a company that specializes in optimizing spare parts management within complex Service Supply Chains. For over 30 years, they have provided a comprehensive predictive platform that replaces uncertainty with clarity and control, helping service leaders ensure the right parts are available at the right time and cost. Their solutions focus on significant cost reduction, real-time optimization, and enhancing customer satisfaction through predictive analytics and inventory management.
🔥 50 minutes ago
Where this job comes from
Posted on Baxter Planning's careers page, not through a job board
First seen by Remote Rocketship 50 minutes ago
Still open on Baxter Planning's site. Checked 39 minutes ago.

201 - 500 employees
Founded 1993
📦 Logistics
💼 Consulting
☁️ SaaS
💰 Corporate Round on 2017-10
Logistics • Consulting • SaaS
Baxter Planning is a company that specializes in optimizing spare parts management within complex Service Supply Chains. For over 30 years, they have provided a comprehensive predictive platform that replaces uncertainty with clarity and control, helping service leaders ensure the right parts are available at the right time and cost. Their solutions focus on significant cost reduction, real-time optimization, and enhancing customer satisfaction through predictive analytics and inventory management.
• Build the data-serving layer, including curated datasets, marts, and product-ready tables • Develop incremental and micro-batch pipelines • Support CDC near-real-time ingestion using AWS DMS • Design BI-friendly star-schema data models and manage schemas • Build ETL/ELT pipelines in Python with Polars • Serve and query data via Athena and/or Redshift • Implement data quality and observability for freshness, completeness, duplicates, schema drift, and anomalies • Orchestrate workflows with Airflow and AWS-native tools such as Step Functions • Contribute to CI/CD, infrastructure as code, architecture discussions, and best practices • Work closely with engineers and stakeholders
• 4+ years building and operating production data pipelines • Strong Python; async/concurrency is a plus • Strong AWS experience across S3, Glue, Athena, Redshift, Lake Formation, CloudWatch, DMS, Lambda, Step Functions, SQS/SNS, ECS, DynamoDB, and CloudFormation • Experience with lakehouse tables such as Delta or similar • Experience with schema evolution, partitioning, compaction, and upserts/merge • Solid data modeling skills, including star schema • Commitment to testing and data quality • Experience running AWS DMS in production, including monitoring and troubleshooting • Fluency in English is requested in the application • Residency in Spain is requested in the application
• Private health insurance • Gym membership • Learning opportunities • Flexible benefits • Team events • Free office snacks and drinks
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