Data Engineer

CERBERO AXIOS LLC
United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$105,000.0 - $140,000.0
Working hours
Regular working hours
Job source

Tech stack

Airflow Amazon Web Services Business Logic BigQuery Cloud Database Data Architecture Information Engineering Data Integration Extract Transform Load (ETL) Data Structures Data Warehousing Relational Databases
+11 more
Database Queries Document-Oriented Databases Python (Programming Language) SQL Databases Data Ingestion Snowflake Software Troubleshooting Backend Data Management Api Design Data Pipelines

Job description

You will join the engineering team behind our new mid-market analytics platform, building the data foundations that power reporting, dashboards, and product insights. You will work across data pipelines, integrations, and storage, helping turn data from different sources into reliable, well-structured information that customers and internal teams can use with confidence., * Design, build, and maintain reliable data pipelines for the analytics platform

  • Develop data ingestion and transformation processes for multiple data sources
  • Work with backend engineers and analysts to define data structures that support reporting and analytics use cases
  • Improve data quality, consistency, and reliability across the platform
  • Build and optimize SQL-based data transformations and workflows
  • Monitor data pipelines and investigate failures, performance issues, and unexpected data behavior
  • Contribute to data architecture and help establish scalable practices as the platform grows
  • Document data models, pipelines, and important business logic so others can work confidently with the data
  • Collaborate with product and engineering teams to understand how data should support new product capabilities

Requirements

  • 3+ years of professional experience in data engineering or a closely related role
  • Strong SQL skills and experience working with relational databases
  • Hands-on experience building and maintaining data pipelines
  • Experience with Python or another language commonly used for data engineering
  • Understanding of data modeling, ETL/ELT processes, and data quality practices
  • Experience working with cloud-based data infrastructure
  • Strong troubleshooting and analytical skills
  • Ability to explain technical decisions clearly and collaborate with engineers, analysts, and product stakeholders
  • Comfortable working independently in a remote, cross-functional environment

NICE TO HAVE

  • Experience with AWS or GCP
  • dbt, Airflow, Dagster, or similar data tooling
  • Experience with modern data warehouses such as Snowflake, BigQuery, or Redshift
  • Experience working with APIs and third-party data integrations
  • Familiarity with analytics, reporting, or business intelligence products
  • Previous B2B SaaS experience
  • Experience working with large or rapidly changing datasets

Benefits & conditions

Compensation will be discussed during the interview process and determined based on experience, technical expertise, and overall fit for the role.

CerebriOS offers a remote-first working environment, professional development opportunities, and a benefits package designed to support our team. Full details of compensation, benefits, and other employment terms will be discussed during the interview process.

About the company

CerebriOS is a software company building B2B SaaS products that help businesses make better decisions, streamline operations, and get more value from their data. Our products combine practical business workflows with intuitive technology designed for everyday use.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

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Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

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Structuring and scaling the backend engineering team

Stefan Lingler Stefan Lingler +1 · Coffee With Developers

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Leveraging BigQuery ML for scalable SQL-based segmentation experiments

Julian Joseph · LIVE

2:57 min

Core technical practices for robust data engineering

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

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Audience questions on AI agents and pipeline vectorization

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