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# Data Engineer

- **Company:** Synergize Consulting Ltd
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** Profiling, Data Validation, Data Conversion, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Profiling, Elasticsearch, JSON, Python (Programming Language), Systems Integration, Extensible Markup Language (XML), Data Processing, Data Ingestion, Semi-structured Data, Kibana, Data Pipelines, Data Generation
- **Published:** August 19, 2026
- **Apply:** https://computerjobs.com/us/en/mob/job/FFFBAF4B573EB526E6

## About the Role

* A solid background in data engineering and pipeline development.
 * Strong, hands-on Python development experience.
 * Experience developing ETL/ELT, ingestion or data integration pipelines.
 * Experience with data transformation, including XML and JSON.
 * Experience with Elasticsearch and/or Kibana.
 * Previous experience of working within a highly regulated environment, for example the public sector or areas of law enforcement.
 * Understanding of data profiling, validation and quality.
 * Experience implementing data ingestion, conversion and integration processes.
 * Experience supporting testing and development through synthetic data generation.
 * Ability to work effectively across technical and operational teams.
 * Strong communication skills, both written and verbal
 * Due to the nature of the client, it would be an advantage for candidates to hold, or be eligible and willing to undergo, a certain level of security clearance (SC/NPPV3)

## Description

* Designing, developing and maintaining data ingestion and ETL/ELT pipelines.
 * Developing robust Python-based data engineering solutions.
 * Profiling, transforming and validating structured and semi-structured data.
 * Working with XML and JSON data and developing schema mapping and transformation processes.
 * Implementing data conversion and integration routes to support the movement of data between systems.
 * Developing and supporting data pipelines within secure environments.
 * Developing synthetic data to support testing, development and integration activities.
 * Building automation to improve data processing and engineering workflows.
 * Supporting the testing and validation of data pipelines and integrations.


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