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# Data engineer

- **Company:** Diverse Lynx LLC
- **Location:** Cleveland, OH, United States (Remote available)
- **Experience:** Expert
- **Salary:** $60,000.0 - $90,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Microsoft Azure, Big Data, BigQuery, Cloud Computing, Code Review, Continuous Integration, Information Engineering, Data Integration, Data Systems, Data Warehousing, Database Design, Distributed Computing Environment, Apache Hadoop, Python (Programming Language), PostgreSQL, Lynx, MySQL, NoSQL, Software Tools, Standard Sql, Data Processing, Snowflake, Apache Spark, Database Performance, Git, Data Lakes, Apache Kafka, Restful APIs, Stream Processing, Data Pipelines
- **Published:** May 14, 2026
- **Apply:** https://www.careerjet.com/jobad/us75ff2688b3de128fb4649d0dda78b748

## About the Role

Strong proficiency in Python for data engineering and automation.
Experience building ETLELT pipelines using tools frameworks.
Strong knowledge of SQL and database design principles.
Hands-on experience with relational and NoSQL databases such as PostgreSQL| MySQL.
Experience with cloud platforms such as AWS| Azure| or GCP.
Familiarity with data warehousing solutions like Snowflake| Redshift| Big Query| or Synapse.
Experience with big data and distributed processing tools such as Spark| Hadoop| or Kafka.
Understanding of REST APIs and data integration patterns.
Knowledge of Git| CICD pipelines| and agile development methodologies
Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.

## Description

Design| develop| test| and maintain scalable data pipelines and data processing systems.
Build and optimize ETLELT workflows for ingesting| transforming| and loading large datasets from multiple sources.
Develop and maintain data warehouses| data lakes| and data integration solutions.
Collaborate with data analysts| data scientists| product managers| and software engineers to support analytics and business needs.
Ensure data quality| integrity| security| and governance across platforms. Optimize database performance| query efficiency| and pipeline reliability.
Implement automation for data workflows| monitoring| and alerting.
Work with batch and real-time data processing frameworks.
Contribute to architecture discussions| code reviews| and best practices for scalable data systems.
Create and maintain technical documentation for pipelines| schemas| and processes. Stay current with emerging data engineering tools| cloud technologies| and industry trends.


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