Data Engineer

Entrebyte Technologies; United States; Remote; USD 39,000 - 54,000; Full time

Job summary

Entrebyte Technologies seeks a data engineer to build and operate the data pipelines and cloud warehouses behind analytics projects. You will bring together imperfect source data, shape it into dependable models, and make it useful for dashboards and reporting.

The role also covers data quality, production support, and helping clients understand their data after handover, including documenting sources and definitions to support ongoing self-service.

Qualifications

• At least four years of data engineering experience with strong SQL and production Python.
• Hands-on experience with a cloud data warehouse and a workflow orchestration tool.
• Solid dimensional modelling skills, including the ability to explain and defend design choices.
• Experience ingesting data from unreliable or constrained sources, such as file drops, legacy databases, and rate-limited APIs.
• Comfort owning pipelines in production, including on-call support for systems you build.
• Awareness of POPIA and appropriate handling of personal information in data pipelines.

Responsibilities

• Create ELT pipelines that bring data from business systems, operational databases, and third-party APIs into cloud warehouses.
• Organize warehouse models into staging, core, and reporting layers using clear dimensional designs.
• Add data quality checks that surface failed or incorrect loads promptly.
• Set up orchestration, alerts, and cost monitoring for production pipelines.
• Work with analysts and clients to turn reporting questions into useful data models.
• Document sources, transformations, and definitions to support ongoing self-service.

Skills

SQL

Python

Cloud data warehouse

Orchestration tools

Dimensional modelling

Production on-call support

Data quality

Data ingestion from unreliable sources

Tools

dbt

Airflow

Job description

Role overview

Build and operate the data pipelines and cloud warehouses behind analytics projects. You will bring together imperfect source data, shape it into dependable models, and make it useful for dashboards and reporting. The work also includes data quality, production support, and helping clients understand their data after handover.

Responsibilities

• Create ELT pipelines that bring data from business systems, operational databases, and third-party APIs into cloud warehouses.
• Organize warehouse models into staging, core, and reporting layers using clear dimensional designs.
• Add data quality checks that surface failed or incorrect loads promptly.
• Set up orchestration, alerts, and cost monitoring for production pipelines.
• Work with analysts and clients to turn reporting questions into useful data models.
• Document sources, transformations, and definitions to support ongoing self-service.

Requirements

• At least four years of data engineering experience, with strong SQL and production Python skills.
• Hands-on experience with a cloud data warehouse and a workflow orchestration tool.
• Solid dimensional modelling skills, including the ability to explain and defend design choices.
• Experience ingesting data from unreliable or constrained sources, such as file drops, legacy databases, and rate-limited APIs.
• Comfort owning pipelines in production, including on-call support for systems you build.
• Awareness of POPIA and appropriate handling of personal information in data pipelines.

Nice to have

• dbt experience, including repository-based tests and documentation.
• Streaming or change data capture for near-real-time ingestion.
• Exposure to machine learning feature pipelines or model deployment.
• Experience presenting findings to client stakeholders.

Benefits and work setup

• Full-time, remote role based in South Africa.