AWS Data Science – Specialist

Job not on LinkedIn

🕒 May 21

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 63%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Compass

WebsiteLinkedInAll Job Openings

10,000+ employees

🏠 Real Estate

📱 Media

Real Estate • Media

Compass is a real-estate-focused content and services site that provides detailed market analysis, buying/selling/renting guides, mortgage and financing information, and home improvement and renovation advice. The site offers resources for homebuyers, sellers, renters, agents, and real estate investors — including articles on appraisals, affordable housing, investment strategies, staging and property maintenance. Compass aims to help users make informed decisions across the housing lifecycle through timely market updates and practical how-to content.

📋 Description

• Lead the development and evolution of Feature Store capabilities: data lineage, feature views, feature recommendation, and new query engines • Design and implement Apache Iceberg tables with a focus on read performance, versioning, and schema evolution • Architect and optimize the serving layer using Redis for real-time features with strict latency SLOs • Integrate and optimize Amazon EMR as a query and large-scale processing engine • Define and implement feature selection and transformation pipelines with end-to-end traceability • Establish quality, versioning, and governance standards for features across the platform • Serve as a technical reference for data and data science teams consuming the Feature Store

🎯 Requirements

• Expertise in feature engineering within enterprise ML platforms (Feast, Tecton, Hopsworks, or equivalents) • Advanced proficiency in Apache Spark/PySpark for large-scale distributed processing • Deep knowledge of Apache Iceberg and lakehouse architectures, including comparisons with Delta Lake and Hudi • Expertise in Redis for low-latency feature serving, including cache invalidation and efficient serialization • Strong production experience with AWS data services: S3, Glue, EMR, Redshift, and Athena • Preferred: experience with data lineage and metadata catalogs (DataHub, OpenMetadata, Marquez) in production • Preferred: experience with Amazon EMR, cluster configuration and optimization, and Spark job tuning • Preferred: expertise in MLOps practices focused on versioning and traceability of data artifacts • Preferred: prior experience in a financial context handling high-cardinality, high-frequency data and regulatory requirements • Preferred: familiarity with at-scale data quality tools (Great Expectations, Soda, dbt tests)