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# Cleared Data Engineer

- **Company:** Accenture
- **Location:** Washington, DC, United States
- **Salary:** $93,400.0 - $176,200.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Amazon S3, Cloud Computing, Cloud Database, Cloud Storage, Databases, Information Engineering, Data Governance, Extract Transform Load (ETL), Dataspaces, Data Systems, Elasticsearch, Data Flow Control, Apache Hadoop, Python (Programming Language), Scrum Methodology, SQL Databases, Data Processing, Google Cloud, Azure Data Factory, Snowflake, Apache Spark, Build Management, Containerization, Pyspark, Kubernetes, AWS Glue, Google Bigquery, Apache Nifi, Data Management, Data Pipelines, Docker, Elk Stack, Amazon Redshift, Databricks
- **Published:** July 22, 2026
- **Apply:** https://dejobs.org/x/x/4EF21E8072A34917B90AA2AB1C12EFBA/job/

## About the Role

* Experience with cloud-based ETL services (e.g. AWS Glue, Google Cloud Dataflow, Azure Data Factory)
 * Experience with Cloud data warehousing technologies (e.g. Amazon Redshift, Google BigQuery, Snowflake)
 * Experience with Python, SQL, Spark, and PySpark
 * Experience with data platforms like Databricks, Palantir, and Snowflake
 * Familiarity with data orchestration and data quality processes

Bonus points if you have:

 * Experience working with federal clients
 * Experience with Docker/Kubernetes Hadoop/Spark, NiFi, ELK stack
 * Experience with Agile / Scrum
 * Experience with COTS and open-source data engineering tools such as ElasticSearch and NiFi
 * Data engineering certification such as Palantir Foundry Data Engineer, Azure Data Engineer Associate, Google Professional Data Engineer, IBM Certified Data Engineer, or similar

Security Clearance:

 * Active Top Secret or TS/SCI or TS/SCI with polygraph clearance

## Description

* Pipeline Architect : Design, build, and maintain scalable end-to-end data pipelines using Databricks, Spark, and related technologies.
 * Transformation Titan : Develop efficient data processing and transformation workflows to support analytics and reporting needs.
 * Integration Hero : Integrate diverse data sources including APIs, databases, and cloud storage into unified datasets.
 * Collaboration Champion : Work closely with cross-functional teams (data science, analytics, business units) to design and implement data solutions that align with business goals.
 * Quality Guardian : Implement robust validation, monitoring, and observability processes to ensure data accuracy, completeness, and reliability.
 * Automation Avenger : Contribute to data governance, security, and automation initiatives within the data ecosystem.
 * Cloud Commander : Leverage AWS services (e.g., S3, Glue, Lambda, Redshift) to build and deploy data solutions in a cloud-native environment.


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