[Remote] Data Engineer at Monte Carlo Data

United States

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$180,000 – $220,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Data Management, AI, SaaSIndustries

Requirements

Candidates should have over 5 years of experience building production-grade data pipelines and backend services, with strong expertise in Python and SQL. Familiarity with AWS technologies and modern data warehouses such as Snowflake, BigQuery, or Redshift is required. Experience with distributed architectures, an ownership mindset, urgency, and customer focus are also essential. PySpark experience is a plus, as is experience with Spark, Airflow, and Infrastructure as Code (IaC) solutions on AWS, Databricks, and Snowflake.

Responsibilities

The Data Engineer will be responsible for ingesting and transforming raw customer data into high-quality datasets. They will design, build, and maintain scalable data pipelines and orchestration workflows, and preprocess metrics and metadata for anomaly detection and lineage models. This role involves collaborating with Data Science and Analytics teams to productionize models and dashboards, continuously improving pipeline reliability by using Monte Carlo's product, and managing and creating data platform resources like database objects and AWS resources.

Skills

Data Pipelines

Backend Services

Python

SQL

PySpark

AWS

Snowflake

BigQuery

Redshift

Distributed Architectures

Spark

Monte Carlo Data

Provides end-to-end data observability solutions

About Monte Carlo Data

Monte Carlo Data helps businesses ensure the reliability of their data through end-to-end data observability, allowing real-time monitoring of data freshness, volume, schema, and quality. Their platform includes tools for incident detection and resolution, which assist analysts in addressing data quality issues efficiently. By integrating with communication tools like Slack and JIRA, it fits seamlessly into existing data management processes. The goal is to help businesses avoid the costs associated with bad data, making it suitable for data-dependent companies across various industries.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$229.6MTotal Funding

SERIES_DCompany Stage

Data & Analytics, AI & Machine LearningIndustries

201-500Employees