Data Engineer

Careerswift - United States - original posting ->
Status
Open
Remote policy
Remote
Employment type
Not stated
Salary
Not stated
Categories
Data-Engineer, Data-Engineer-Jobs, Data-Engineering, Data-Engineering-Specialist, Data-Engineering-Jobs, Data-Engineering-Positions
Tech
awsgcpbigquerysnowflakeairflowpythonremote-countrydata
Source
himalayas
First observed
2026-08-28 19:16 UTC
Last seen
2026-08-28 19:16 UTC
Source claims posted
2026-08-28 18:51 UTC
Consecutive misses
1 of 10

What the posting says

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.

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.

WHAT YOU WILL DO

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

WHAT WE ARE LOOKING FOR

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

COMPENSATION AND BENEFITS

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.

HIRING PROCESS

Application review → introductory conversation → technical discussion → conversation with the team → offer.

We aim to keep the process focused and respectful of your time, with clear communication throughout the process.

EQUAL OPPORTUNITY

CerebriOS is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.

Location: Remote

Salary Range: 105,000 - 140,000 USD (gross, annually)

Originally posted on Himalayas

Quality

Completeness: 65%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #425694 2026-08-28 19:16 UTC
    Published
  2. o
    #427434 2026-08-28 21:19 UTC
    Not seen
    Miss 1 in a row