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Remote Amazon Data Engineer Jobs in Washington, DC

Sparibis

Data Engineer

Washington, DC · On-site +1

$129K - $155K/yr

Location: 100% Remote Years' Experience: 5+ years Professional Experience Education: Bachelor ... ensure high data quality. * Support AI/ML teams with optimizing feature engineering code.

Node.Digital

Senior Data Engineer

Washington, DC · On-site +1

$120K - $163K/yr

Herndon, VA (Remote Work) Must have an Public Trust Clearance KEY RESPONSIBILITIES • Provide authoritative expertise on data engineering methods and best practices, including code first development ...

Node.Digital

Senior Data Engineer

Washington, DC · Remote

$120K - $163K/yr

Herndon, VA (Remote Work) Must have an Public Trust Clearance KEY RESPONSIBILITIES Provide authoritative expertise on data engineering methods and best practices, including code first development ...

TeamWorx Security, LLC.

Senior Data Engineer

Columbia, MD · Remote

$105K - $142K/yr

Location:Fully Remote, United States Position Type: Full-Time Clearance: U.S. citizenship is ... The Senior Data Engineer will work with technical teams, program leadership, and government ...

Node.Digital

Senior Data Engineer

Washington, DC · Remote

$108K - $147K/yr

Herndon, VA (Remote Work) Must have an Public Trust Clearance KEY RESPONSIBILITIES * Provide authoritative expertise on data engineering methods and best practices, including code first development ...

540

Senior Data Engineer

Arlington, VA · Remote

$121K - $165K/yr

Remote within the continental United States. Periodic travel may be required Citizenship ... Senior Data Engineer WHY 540? 540 is a forward-thinking company that the government turns to in ...

Eliassen Group

ETL Data Engineer

Tysons, VA · Remote

$70 - $88/hr

Hybrid 3 days onsite / 2 days remote in Mclean, VA Our client seeks an ETL Data Engineer to build ... Experience with foundation model APIs such as Anthropic Claude, Amazon Nova, or OpenAI.

Capital One

Sr. Staff Data Engineer

Mclean, VA · On-site +1

$107K - $145K/yr

Remote (Regardless of Location): $286,200 - $326,700 for Sr Distinguished Data Engineer McLean, VA: $314,800 - $359,300 for Sr Distinguished Data Engineer New York, NY: $343,400 - $392,000 for Sr ...

System One

AWS Cloud Data Engineer

Mclean, VA · Remote

AWS Cloud Data Engineer Location: McLean, VA Type: Long-term contract Work Model ... Remote Hours: 40.0 Security Clearance: Ability to obtain a Federal Public Trust clearance Contact:

System One

AWS Cloud Data Engineer

Mclean, VA · Remote

AWS Cloud Data Engineer Location: McLean, VA Type: Long-term contract Work Model ... Remote Hours: 40.0 Security Clearance: Ability to obtain a Federal Public Trust clearance Contact:

System One

AWS Cloud Data Engineer

Mclean, VA · Remote

AWS Cloud Data Engineer Location: McLean, VA Type: Long-term contract Work Model ... Remote Hours: 40.0 Security Clearance: Ability to obtain a Federal Public Trust clearance Contact:

System One

AWS Cloud Data Engineer

Mclean, VA · Remote

AWS Cloud Data Engineer Location: McLean, VA Type: Long-term contract Work Model ... Remote Hours: 40.0 Security Clearance: Ability to obtain a Federal Public Trust clearance Contact:

System One

AWS Cloud Data Engineer

Mclean, VA · Remote

AWS Cloud Data Engineer Location: McLean, VA Type: Long-term contract Work Model ... Remote Hours: 40.0 Security Clearance: Ability to obtain a Federal Public Trust clearance Contact:

System One

AWS Cloud Data Engineer

Mclean, VA · Remote

AWS Cloud Data Engineer Location: McLean, VA Type: Long-term contract Work Model ... Remote Hours: 40.0 Security Clearance: Ability to obtain a Federal Public Trust clearance Contact:

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Showing results 41-60

All JobsAmazon Data Engineer JobsRemote Amazon Data Engineer JobsRemote Amazon Data Engineer Jobs in Washington, DC

Remote Amazon Data Engineer information

See Washington, DC salary details

$50.4K

$146.9K

$201K

How much do remote amazon data engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for remote amazon data engineer in Washington, DC is $146,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,700.00 and $155,700.00 per year, depending on experience, location, and employer.

What does a remote Amazon data engineer do?

A Remote Amazon Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and databases for Amazon or companies using Amazon Web Services (AWS). They work remotely to process large volumes of data, ensure data quality, and enable efficient data analysis. Their tasks typically include extracting data from various sources, transforming it into usable formats, and loading it into data warehouses or analytics platforms. They often use AWS tools such as Redshift, Glue, S3, and Lambda to manage infrastructure and automate workflows. Strong programming skills in languages like Python or SQL are essential for this role.

What are the key skills and qualifications needed to thrive as a remote Amazon data engineer, and why are they important?

To thrive as a Remote Amazon Data Engineer, you need strong expertise in data modeling, ETL development, SQL, and programming languages such as Python or Java, typically supported by a degree in computer science or a related field. Familiarity with AWS services like Redshift, S3, Glue, and data pipeline tools, as well as certifications such as AWS Certified Data Analytics, are highly valued. Excellent problem-solving, communication, and self-management skills help remote engineers collaborate effectively and deliver reliable data solutions. These abilities are crucial for ensuring robust, scalable data infrastructure and supporting data-driven decision-making in a distributed work environment.

What are some common challenges faced by remote Amazon data engineers, and how can they be addressed?

Remote Amazon Data Engineers often encounter challenges related to collaborating across time zones and ensuring clear communication with global teams. Effective use of collaboration tools, regular virtual meetings, and clear documentation can help bridge these gaps. Additionally, managing large-scale data pipelines on AWS requires staying updated on best practices for security, scalability, and cost optimization. Proactively participating in team stand-ups and engaging in continuous learning about AWS services can significantly enhance productivity and project outcomes.

What is the difference between Remote Amazon Data Engineer vs Remote Amazon Data Analyst?

AspectRemote Amazon Data EngineerRemote Amazon Data Analyst
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentDesigning data pipelines, managing ETL processesInterpreting data, creating reports and dashboards
Employer & Industry UsageTech companies, e-commerce, cloud servicesRetail, marketing, e-commerce
Common Search & ComparisonFocus on data infrastructure and pipelinesFocus on data insights and reporting

The main difference between a Remote Amazon Data Engineer and a Remote Amazon Data Analyst lies in their roles. Data Engineers build and maintain data pipelines and infrastructure, requiring technical skills in data architecture. Data Analysts interpret data to generate insights, focusing on analysis and reporting. Both roles are essential in data-driven companies but serve different functions within the data ecosystem.

Can I work remotely as a remote amazon data engineer?

Yes, many Amazon Data Engineer roles are available as remote positions, allowing professionals to work from home or other locations. These roles typically require strong skills in data pipelines, cloud platforms like AWS, and relevant certifications, with companies often providing remote work options depending on the team and project needs.

How much do remote Amazon data engineers make?

Remote Amazon data engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and skill set. Salaries can vary based on factors such as certifications, expertise in tools like AWS and Spark, and the level of seniority in the role.

What are the most commonly searched types of Amazon Data Engineer jobs in Washington, DC?

The most popular types of Amazon Data Engineer jobs in Washington, DC are:

What are popular job titles related to Remote Amazon Data Engineer jobs in Washington, DC?

For Remote Amazon Data Engineer jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Remote Amazon Data Engineer jobs in Washington, DC look for?

The top searched job categories for Remote Amazon Data Engineer jobs in Washington, DC are:

Remote Amazon Data Engineer jobs near you

Data Engineer

Sparibis

Washington, DC • On-site, Remote

$129K - $155K/yr

Full-time

Re-posted 16 days ago

Job description

Location: 100% Remote
Years' Experience: 5+ years Professional Experience
Education: Bachelor's Degree in IT related field
Clearance: Applicants must be able to obtain and maintain a secret security clearance. United States Citizenship is required as part of the eligibility criteria to be able to obtain this type of security clearance.
Required Certifications:
  • CompTIA Security +

Key Skills:
  • 5+ years of IT experience focusing on enterprise data architecture and management to include data flow charts, diagrams, and other technical documentation.
  • Experience with Databricks, Structured Streaming, Delta Lake concepts, and Delta Live Tables required.
  • Python development experience required.
  • Experience with ETL and ELT tools such as SSIS, Pentaho, and/or Data Migration Services, and the ability to incorporate Python as required.
  • Advanced level SQL experience (Joins, Aggregation, Windowing functions, Common Table Expressions, RDBMS schema design, Postgres performance optimization).
  • Proficiency using Git for version control, including repository management, branching, merging, and pull requests.
  • Active CompTIA Security+ certification preferred. If selected, must be able to obtain a CompTIA Security+ certification prior to beginning supporting the program.

Responsibilities
  • Plan, create, and maintain data architectures, ensuring alignment with business requirements.
  • Obtain data, formulate dataset processes, and store optimized data.
  • Identify problems and inefficiencies and apply solutions.
  • Determine tasks where manual participation can be eliminated with automation.
  • Identify and optimize data bottlenecks, leveraging automation where possible.
  • Create and manage data lifecycle policies (retention, backups/restore, etc).
  • In-depth knowledge for creating, maintaining, and managing ETL/ELT pipelines.
  • Create, maintain, and manage data transformations.
  • Maintain/update documentation.
  • Create, maintain, and manage data pipeline schedules.
  • Monitor data pipelines.
  • Create, maintain, and manage data quality gates (Great Expectations) to ensure high data quality.
  • Support AI/ML teams with optimizing feature engineering code.
  • Expertise in Spark/Python/Databricks, Data Lake and SQL.
  • Create, maintain, and manage Spark Structured Steaming jobs, including using the newer Delta Live Tables and/or DBT.
  • Research existing data in the data lake to determine best sources for data.
  • Create, manage, and maintain ksqlDB and Kafka Streams queries/code
  • Data driven testing for data quality.
  • Maintain and update Python-based data processing scripts executed on AWS Lambdas.
  • Unit tests for all the Spark, Python data processing and Lambda codes.
  • Maintain PCIS Reporting Database data lake with optimizations and maintenance (performance tuning, etc).
  • Streamlining data processing experience including formalizing concepts of how to handle lake data, defining windows, and how window definitions impact data freshness.

Qualifications
  • 5+ years of IT experience focusing on enterprise data architecture and management.
  • Must have an active Secret security clearance.
  • Bachelor degree required.
  • CompTIA Security+ certification preferred. If selected, must be able to obtain a CompTIA Security+ certification prior to begin supporting the program.
  • Experience in Conceptual/Logical/Physical Data Modeling & expertise in Relational and Dimensional Data Modeling.
  • Experience with Databricks and Python Development, Structured Streaming, Delta Lake concepts, and Delta Live Tables required.
    • Additional experience with Spark, Spark SQL, Spark DataFrames and DataSets, and PySpark.
    • Data Lake concepts such as time travel and schema evolution and optimization.
    • Structured Streaming and Delta Live Tables with Databricks a bonus.
  • Knowledge of Python (Python 3.X) for CI/CD pipelines required.
    • Familiarity with Pytest and Unittest a bonus.
  • Experience leading and architecting enterprise-wide initiatives specifically system integration, data migration, transformation, data warehouse build, data mart build, and data lakes implementation / support.
    • Advanced level understanding of streaming data pipelines and how they differ from batch systems.
    • Formalize concepts of how to handle late data, defining windows, and data freshness.
    • Advanced understanding of ETL and ELT and ETL/ELT tools such as SSIS, Pentaho, Data Migration Service etc.
    • Understanding of concepts and implementation strategies for different incremental data loads such as tumbling window, sliding window, high watermark, etc.
    • Familiarity and/or expertise with Great Expectations or other data quality/data validation frameworks a bonus.
    • Understanding of streaming data pipelines and batch systems.
    • Familiarity with concepts such as late data, defining windows, and how window definitions impact data freshness.
  • Advanced level SQL experience (Joins, Aggregation, Windowing functions, Common Table Expressions, RDBMS schema design, Postgres performance optimization).
  • Indexing and partitioning strategy experience.
  • Debug, troubleshoot, design and implement solutions to complex technical issues.
  • Experience with large-scale, high-performance enterprise big data application deployment and solution.
  • Understanding how to create DAGs to define workflows.
  • Familiarity with CI/CD pipelines, containerization, and pipeline orchestration tools such as Airflow, Prefect, etc a bonus but not required.
  • Architecture experience in AWS environment a bonus.
    • Familiarity working with Kinesis and/or Lambda specifically with how to push and pull data, how to use AWS tools to view data in Kinesis streams, and for processing massive data at scale a bonus.
    • Experience with Docker, Jenkins, and CloudWatch.
    • Ability to write and maintain Jenkinsfiles for supporting CI/CD pipelines.
    • Experience working with AWS Lambdas for configuration and optimization.
    • Experience working with DynamoDB to query and write data.
    • Experience with S3.
  • Experience working with JSON and defining JSON Schemas a bonus.
  • Experience setting up and management Confluent/Kafka topics and ensuring performance using Kafka a bonus.
    • Familiarity with Schema Registry, message formats such as Avro, ORC, etc.
    • Understanding how to manage ksqlDB SQL files and migrations and Kafka Streams.
  • Ability to thrive in a team-based environment.
  • Experience briefing the benefits and constraints of technology solutions to technology partners, stakeholders, team members, and senior level of management.
  • Proficiency using Git for version control, including repository management, branching, merging, and pull requests.
    • Repository setup and management.
    • Branching strategies (feature, develop, main).
    • Merging and resolving conflicts.
    • Creating and reviewing pull requests.
    • Commit best practices (clear messages, atomic commits).
    • Tagging and release management.

About Sparibis
Sparibis LLC is a professional solution firm that Clients rely on to access the best talent to drive their business success.
Sparibis is an equal opportunity employer that values diversity at all levels. All individuals, regardless of personal characteristics, are encouraged to apply.

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