> Markdown version of [/jobs/ext/4397733-data-engineer](https://www.wearedevelopers.com/jobs/ext/4397733-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer

- **Company:** Limetaya Technology LLC
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $96,000.0 - $131,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, BigQuery, Cloud Computing, Code Review, Databases, Continuous Integration, Data Validation, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Warehousing, Relational Databases, Database Queries, DevOps, Programming Tools, Document-Oriented Databases, Github, Revision Control Systems, Python (Programming Language), Power BI, Software Tools, Standard Sql, Software Engineering, SQL Databases, Tableau (Software), Workflow Management Systems, Data Processing, Scripting, Google Cloud, Data Storage Technologies, Cloud Platform System, Snowflake, Apache Spark, Git, Microsoft Fabric, Information Technology, Data Analytics, Software Version Control, Data Pipelines, Databricks, Programming Languages
- **Published:** October 15, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b83ddeac3e7f802c

## About the Role

* Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
 * 2+ years of experience in data engineering, data analytics, or a related technical role.
 * Working knowledge of SQL, including writing queries, joining tables, filtering data, and working with relational databases.
 * Experience with Python or a similar programming language for data manipulation, scripting, or automation.
 * Understanding of data engineering fundamentals, including data pipelines, data integration, and ETL/ELT processes.
 * Familiarity with relational databases, data warehousing concepts, and basic data modeling techniques.
 * Exposure to a cloud platform such as AWS, Microsoft Azure, or Google Cloud Platform.
 * Familiarity with Git, GitHub, or similar version control tools and an understanding of software development practices.
 * Strong analytical, problem-solving, and troubleshooting skills, with attention to data quality and detail.
 * Good written and verbal communication skills and the ability to collaborate with technical and non-technical team members., * Exposure to data engineering platforms or tools such as Databricks, Apache Spark, Snowflake, BigQuery, or Microsoft Fabric.
 * Familiarity with data transformation and orchestration tools such as dbt, Apache Airflow, or similar technologies.
 * Basic understanding of CI/CD, automated testing, monitoring, and data pipeline scheduling.
 * Experience with business intelligence tools such as Power BI or Tableau.
 * Interest in learning new data technologies and applying modern development tools to improve productivity.

## Description

You will collaborate with experienced data engineers, analysts, and other technical and business stakeholders to understand data requirements, develop efficient data processing solutions, and maintain data quality across systems. This position offers an opportunity to contribute to real-world data engineering projects while strengthening your skills in cloud-based data platforms, data warehousing, automation, and modern engineering practices., * Develop, test, and maintain data pipelines to collect, transform, and integrate data from databases, APIs, files, and other sources.

 * Write and optimize SQL queries and use Python to support data processing, transformation, validation, and automation.
 * Assist in building and maintaining ETL/ELT workflows that deliver accurate, consistent, and analytics-ready datasets.
 * Work with cloud-based data platforms and data warehouses to support data storage, processing, and integration requirements.
 * Monitor data pipelines, investigate data discrepancies, troubleshoot processing issues, and support improvements in reliability and performance.
 * Contribute to data modeling and transformation tasks that support reporting, business intelligence, and analytical applications.
 * Apply data quality checks and validation practices to help maintain data accuracy, completeness, and consistency.
 * Use Git-based version control and participate in code reviews, testing, and established development workflows.
 * Assist with deploying data pipeline updates through CI/CD processes and help document data flows, transformations, and technical procedures.
 * Collaborate with data engineers, analysts, and business stakeholders to understand requirements and deliver practical data solutions.