Senior Data Engineer

Job not on LinkedIn

🕒 March 31

🏄 California, Maryland – Remote

🏄 California – Remote 🦀 Maryland – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 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.

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Anagenex

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

💰 $30M Series A on 2022-06

Healthcare • Consulting • Logistics

Anagenex is a company focused on accelerating drug discovery using advanced AI technology and large-scale data. By testing billions of molecules and generating high-quality datasets, Anagenex leverages proprietary neural networks to design and refine new compounds that can potentially treat diseases more efficiently. The company aims to overcome the traditional 25-year timeline from disease protein identification to medicinal application, integrating iterative AI and real laboratory experiments to speed up the process, thereby bringing medicines to patients faster.

📋 Description

• Build and deploy the data pipelines that power Companys machine learning platform. • Develop warehouse architectures that integrate data from diverse sources. • Design analytics solutions for both product development and internal collaborators.

🎯 Requirements

• A minimum of 1 years experience in data engineering, analytics engineering, or software engineering with an emphasis on large scale data management and processing systems. • Proficiency in Python and advanced SQL. • Advanced experience with ETL pipelines, data modeling and managing data warehouses (Snowflake, BigQuery, Redshift, etc). • Experience with SQL RDBMS such as MySQL, Postgres, Oracle, SQL Server, etc., as well as NoSQL systems such as MongoDB is required. • Experience with tools including Meltano, dbt, Airflow, and Superset is required. • Experience with Docker, Git and AWS (EC2, ECS, S3, Step Functions, and Athena). • Analytics and Business Intelligence knowledge is highly preferred. • Experience working with common SaaS APIs (such as CRMs) is preferred.