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Entry Level Azure Data Factory Jobs in Washington, DC

NAVA Software Solutions

Data Scientist

Merrifield, VA · On-site

Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud * Understanding of data models, large datasets, business/technical ...

Data Trust

Data Acquisition Coordinator

Arlington, VA · On-site

$55 - $75/hr

Set up and monitor automated ETL pipelines through Microsoft Azure Data Factory to ensure quick and accurate data import and processing * Utilize Microsoft SQL and Excel to access, sort, organize ...

New

Solomon Page

Snowflake Data Engineer

Washington, DC · On-site

$150K - $190K/yr

Experience building and deploying data platforms in Azure (Azure Data Factory, Azure Storage, Azure AD) * Strong experience writing and optimizing SQL for analytical and financial datasets

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Entry Level Azure Data Factory information

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How much do entry level azure data factory jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for entry level azure data factory in Washington, DC is $66.15, according to ZipRecruiter salary data. Most workers in this role earn between $59.90 and $74.33 per hour, depending on experience, location, and employer.

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Entry Level Azure Data Factory jobs near you

Cleared Data Engineer

Accenture Federal Services

Washington, DC

$129K - $155K/yr

Full-time

Re-posted 29 days ago

Accenture Federal Services rating

8.7

Company rating: 8.7 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

51st of 500 rated business services

Job description

The work: 

  • 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. 

Here's what you need: 

  • 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

 #LI-DataAI

What Accenture Federal Services employees say

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