Cleared Data Engineer
AWS
Aws Data Warehouse
Big Data
Bigdata
Cloud
Cloud Data Engineering
Cloud Data Platform
Cloud Data Warehouse
Cloud Data Warehouse
Cloud Native
Cloud Platform
Cloud Platforms
Cloud Storage
Data Analytics
Data Architecture
Data Engineer
Data Engineering
Data Integration
Data Pipeline
Data Platform
Data Processing
Data Warehouse
Database
Databricks
ETL
Security
Spark
SQL
Job Description
Accenture Federal Services is hiring a Cleared Data Engineer for an onsite role in Washington, DC. In this position, you will design, build, and maintain scalable end-to-end data pipelines and cloud-native data solutions that support analytics and reporting across teams, with the security clearance required for federal work.
What you’ll do
- Design, build, and maintain scalable end-to-end data pipelines using Databricks, Spark, and related technologies.
- Develop data processing and transformation workflows to support analytics and reporting needs.
- Integrate diverse data sources including APIs, databases, and cloud storage into unified datasets.
- Collaborate with cross-functional teams including data science, analytics, and business units to deliver solutions aligned with business goals.
- Implement validation, monitoring, and observability processes to ensure data accuracy, completeness, and reliability.
- Support data governance, security, and automation initiatives within the data ecosystem.
- Use AWS services such as S3, Glue, Lambda, and Redshift to build and deploy cloud-native data solutions.
What you bring
- Experience with cloud-based ETL services (such as AWS Glue, Google Cloud Dataflow, or Azure Data Factory).
- Experience with cloud data warehousing technologies (such as Amazon Redshift, Google BigQuery, or Snowflake).
- Hands-on skills with Python, SQL, Spark, and PySpark.
- Experience with data platforms including Databricks, Palantir, and Snowflake.
- Familiarity with data orchestration and data quality processes.
- Active Top Secret or TS/SCI or TS/SCI with polygraph clearance.
Tools and technologies you may use
- Databricks, Spark, Python, SQL, PySpark
- AWS (S3, Glue, Lambda, Redshift)
- AWS Glue, Google Cloud Dataflow, Azure Data Factory
- Google BigQuery, Snowflake, Palantir
- Docker/Kubernetes, Hadoop/Spark, NiFi, ELK stack, ElasticSearch
Benefits
- 401(k)
- Dental insurance
- Parental leave
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.
- A data engineering certification such as Palantir Foundry Data Engineer, Azure Data Engineer Associate, Google Professional Data Engineer, IBM Certified Data Engineer, or similar.
Pay range: USD 93,400 - 176,200 per year.
Work location: In person.
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