# DATA ENGINEER - 2025-ENC-ST-000392 at Kruger NearShore LLC - Rekluti

> Remote · Dominican Republic · Unspecified · Data engineering · open. Source: https://alderhq.app/jobs/recruitee%3Aeasyapplyrekluti%3A2156549 (read 2026-11-09).

## Facts (observed)

- Company: [Kruger NearShore LLC - Rekluti](https://alderhq.app/companies/kruger-nearshore-llc-rekluti)
- Location text: Santo Domingo, Cibao Nordeste, Dominican Republic
- Where it can be done from (inferred): Remote · Dominican Republic (evidence: "Location: Santo Domingo, Cibao Nordeste, Dominican Republic")
- Posted: 2025-06-01 (526 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://easyapplyrekluti.recruitee.com/o/test-lead-2025-gru-st-000388-2-5
- Skills listed (inferred): Python, Java, Kafka, GCP, Spark, Airflow, dbt, SQL

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

Are you passionate about building scalable data solutions in the cloud? We’re looking for a Data Engineer with strong programming skills and hands-on experience with modern data tools to help us develop high-quality metrics, pipelines, and real-time processing systems.

### Requirements

📌 What You'll Bring

✅ 5+ years of experience in designing and building scalable data lakes in cloud environments.

✅ Advanced programming skills in Python or Java.

✅ Proven experience in ETL/ELT pipeline development, ideally with Airflow.

✅ Expertise in DBT and data warehouse modeling for metrics development.

✅ Solid experience working with real-time data streaming tools like Kafka or Google Pub/Sub.

✅ Hands-on experience with big data processing tools, such as Hadoop, Spark, or their GCP equivalents (e.g., Dataproc, Dataflow). ✅Advanced SQL skills – you know how to write and optimize complex queries across large datasets.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/recruitee%3Aeasyapplyrekluti%3A2156549 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.