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Cloud Data Engineer Entry Level Jobs in Reston, VA

Berkley

Databricks Data Engineer

Manassas, VA · On-site

$114K - $137K/yr

The Databricks Data Engineer will help design, build, deploy, and maintain scalable and production grade data pipelines in modern cloud environments, enabling analytics, AI, ML, and decision ...

Software Guidance & Assistance

Data Engineer

Rockville, MD · On-site

$116K - $140K/yr

The Data Engineer works with moderate supervision across two equally weighted domains: (1) large-scale data pipeline development processing market events in a cloud environment, and (2) design and ...

Omm IT Solutions

Sr Data Engineer

Mclean, VA

$116K - $139K/yr

The ideal candidate combines strong engineering fundamentals with cloud\-native data expertise and is capable of translating complex business needs into robust, performant, and well\-documented data ...

Ardent Principles, Inc

Cloud Engineer

Chantilly, VA · On-site

$57 - $76.25/hr

We offer advanced services in data science, data engineering, software engineering, AI solutions ... Cloud data center environments. * Cyber operations. * Managing and evolving organizational business ...

Aerstone

Data Engineer

Springfield, VA · On-site

$119K - $143K/yr

... cloud data platforms, particularly AWS (S3, Glue, RDS, etc.). • Strong SQL skills and experience with role-based access control in database systems. • Familiarity with scripting or programming ...

Dlapiper

Data Engineer

Reston, VA

$119K - $143K/yr

Together. Summary The Data Engineer, Solutions & Data role designs, builds, and operates data ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Dlapiper

Data Engineer

Washington, DC · On-site

$129K - $155K/yr

Together. Summary The Data Engineer, Solutions & Data role designs, builds, and operates data ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

DLA Piper

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

Together. Summary The Data Engineer, Solutions & Data role designs, builds, and operates data ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Altus Consulting Corp

Data Engineer

Herndon, VA · On-site

$117K - $141K/yr

Experience with Cloud platforms (AWS, Azure, Google Cloud Platform). * Familiarity with data ... Understanding of data engineering principles and best practices. Disclaimer: The information ...

Central Intelligence Agency

Data Engineer

Washington, DC · On-site +1

$74K - $156K/yr

They design and build scalable data pipelines using commercial cloud, open source, and custom software solutions to process large datasets. DDI Data Engineers create automated data validation methods ...

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Cloud Data Engineer Entry Level information

See Reston, VA salary details

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How much do cloud data engineer entry level jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for cloud data engineer entry level in Reston, VA is $65.42, according to ZipRecruiter salary data. Most workers in this role earn between $55.77 and $74.52 per hour, depending on experience, location, and employer.

What does a cloud data engineer entry level do?

A Cloud Data Engineer Entry Level is responsible for assisting in the design, development, and management of data infrastructure on cloud platforms such as AWS, Azure, or Google Cloud. They help build and maintain pipelines that move and transform data, ensuring it is accessible and secure for analysis. Entry-level cloud data engineers often work under the supervision of senior engineers, contributing to data integration, storage solutions, and performance optimization tasks while learning industry best practices.

What are the key skills and qualifications needed to thrive as an entry level cloud data engineer?

To thrive as an Entry Level Cloud Data Engineer, you need a solid understanding of data structures, basic programming (often in Python or SQL), and foundational knowledge of cloud platforms such as AWS, Azure, or Google Cloud, typically supported by a related degree or certification. Experience with cloud-based data warehousing tools (like Amazon Redshift or BigQuery), ETL processes, and data pipeline orchestration systems is highly valuable. Strong analytical thinking, attention to detail, and effective communication skills help you collaborate with teams and solve data-related challenges. These skills and qualities are crucial for efficiently building, managing, and optimizing cloud data solutions that support business analytics and decision-making.

What types of projects and tasks can an entry level cloud data engineer expect to work on during their first year?

As an entry-level Cloud Data Engineer, you can expect to work on foundational tasks such as building and maintaining data pipelines, assisting with cloud platform migrations, and supporting data integration efforts. You'll often collaborate with senior engineers and data analysts to ensure data is properly ingested, transformed, and stored in cloud environments like AWS, Azure, or Google Cloud. Common challenges include learning to troubleshoot data flow issues and adapting to various cloud tools and services. Over time, you'll gain exposure to automation, scripting, and optimizing data workflows, which are essential for career growth in this field.

What are the most commonly searched types of Cloud Data Engineer jobs in Reston, VA?

The most popular types of Cloud Data Engineer jobs in Reston, VA are:

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For Cloud Data Engineer Entry Level jobs in Reston, VA, the most frequently searched job titles are:

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The top searched job categories for Cloud Data Engineer Entry Level jobs in Reston, VA are:

What cities near Reston, VA are hiring for Cloud Data Engineer Entry Level jobs?

Cities near Reston, VA with the most Cloud Data Engineer Entry Level job openings:

Cloud Data Engineer Entry Level jobs near you
Infographic showing various Cloud Data Engineer Entry Level job openings in Reston, VA as of June 2026, with employment types broken down into 88% Full Time, 9% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $136,081 per year, or $65.4 per hour.

Databricks Data Engineer

Berkley

Manassas, VA • On-site

$114K - $137K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 26 days ago

Job description

Company Details
We started in early 2019 as a small group of technologists with a passion for making insurance better. Today we are working with a team of industry experts who run five different insurance brands and collectively control $1 billion in annual premiums.
We believe in an idea and execution meritocracy. In other words, a place where the best ideas win and the people who deliver the most value get the most opportunities.
As we grow our team, we are looking for inquisitive, entrepreneurial people who are excited to reimagine the insurance industry.
Insurance is too complex. Help us make it better.
Responsibilities
This position requires on-site work Monday-Thursday at either our Manassas, VA or Chesterfield, MO location.
The Databricks Data Engineer will help design, build, deploy, and maintain scalable and production grade data pipelines in modern cloud environments, enabling analytics, AI, ML, and decision advantage at scale. This role will work with cutting-edge tools like Databricks, Delta Lake, PySpark, and AI/BI genie to transform raw data into actionable insights. As a hands-on Databricks Data Engineer with deep expertise in Azure Databricks and MLOps, this role will have the opportunity to migrate and translate legacy SSIS ETL logic into scalable, cloud-native data pipelines in Databricks. This role will partner with data engineers, data scientists, and product manager to design features, train/evaluate models, and deploy them to production using MLflow, Databricks and Workflows-with rigorous observability, governance (Unity Catalog), and CI/CD automation.
Data Pipeline Engineering
  • Design, build, and maintain high-performance, scalable ETL/ELT pipelines using Azure Databricks, Delta Lake, and PySpark.
  • Convert and modernize existing SSIS package logic into cloud-native Databricks pipelines using PySpark notebooks, Delta Live Tables (DLT), and Databricks Workflows.
  • Implement reliable batch and streaming pipelines with robust data quality and validation frameworks.
  • Optimize pipeline performance using Photon, efficient file formats, partitioning, Z-ordering, and caching strategies.

Lakehouse Platform Development
  • Develop and manage datasets within Delta Lake, ensuring ACID reliability, schema evolution, versioning, and time travel.
  • Architect feature-rich data layers including:
    • Bronze (raw ingestion)
    • Silver (validated, conformed)
    • Gold (analytics-ready and ML-ready)
  • Implement data governance using Unity Catalog for fine-grained access control, lineage, auditability, and metadata management.

MLOps & ML-Enabled Data Pipelines
  • Partner with data scientists and data engineers to create feature pipelines, model training pipelines, and production scoring pipelines.
  • Deploy and operationalize models using MLflow, Databricks Model Registry, and Databricks Workflows.
  • Use Databricks built-in AI SQL functions such as ai_query, ai_forecast, ai_analyze_sentiment to generate actionable insight from large amount of unstructured or structured raw data
  • Implement monitoring for:
    • Pipeline failures
    • Data/feature drift
    • Model performance degradation
    • Operational SLAs/SLIs/SLOs
  • Build automated CI/CD workflows using GitHub Actions or Azure DevOps for notebook deployment, pipeline testing, and environment promotion.

Data Platform, Data Security & Data Governance
  • Collaborate with data engineers to design reliable data products on Delta Lake; leverage Delta Live Tables (DLT) for declarative pipelines when applicable.
  • Enforce Unity Catalog for lineage, permissions, and audit; manage secrets, tokens, and keys securely (e.g., Databricks secrets, Key Vault/Secrets Manager).

Collaboration & Leadership
  • Work closely with cross-functional teams: data engineering, data scientist, product manager, and business stakeholders.
  • Serve as a Databricks SME-championing best practices, code standards, governance, and reusable frameworks.
  • Document architecture, workflows, data models, runbooks, and operational procedures.

Qualifications
  • Minimum of 3 years of experience in Databricks, PySpark notebooks, Python, DevOps, software development, and data engineering.
  • Certified Databricks Data Engineer Associate or Professional is a plus.

Skills & Competencies
  • Proficient in designing, building, deploying, and maintaining high-performance, scalable ETL/ELT pipelines using Azure Databricks, Delta Lake, and PySpark Notebook.
  • Proficient in building, deploying, and operating production ML models such as supervised, unsupervised, and anomaly detection, including techniques for imbalanced datasets
  • Proficient with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring, drift detection, and automated retraining
  • Proficiency in Python including Pandas and PySpark Dataframes
  • Expert level of SQL skills including Stored Procedure, experience with SSIS, SSRS, Power BI is a plus.
  • Proficient with cloud data engineering platforms, such as Azure, Databricks, Spark, or SQL, and batch and streaming pipelines
  • Familiar with Databricks AI Built-In Functions such as AI_Query, AI_Gen, AI_Classify, AI_Forecast, AI_Analyze_Sentiment, able to use them to extract actionable insights from large amount of unstructured or structured raw data
  • Experience with Python and ML frameworks, such as PyTorch or TensorFlow
  • Experience improving data quality, lineage, and observability in enterprise data environments and operationalizing rules and model-driven scoring for prioritization, routing, or case selection
  • Experience with predictive analytics, machine learning and artificial intelligence desired.

Education
  • A Bachelor's degree in Computer Science, Management Information Systems, Engineering, Math, Physics, or a related quantitative field is required (4-year degree). Master's degree preferred
  • Experience in the commercial insurance industry is a plus.

Additional Company Details
The Company is an equal employment opportunity employer.
We do not accept any unsolicited resumes from external recruiting firms.
The company offers a competitive compensation plan and robust benefits package for full time regular employees.
Base salary & Benefits include Health, dental, vision, life, disability, wellness, paid time off, 401(k) and profit-sharing plans.
-Salary Range: $110k- $140k
The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment.
Additional Requirements
• Ability to travel locally and nationally up to 5% of the time
Sponsorship Details
Sponsorship not Offered for this Role

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