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Remote Amazon Data Engineer Jobs in Virginia (NOW HIRING)

Senior Data Engineer

Mclean, VA · Remote

$107K - $145K/yr

Senior Data Engineer Job Number: 912 This is a remote position. Ad Hoc is a technology company that ... Experience with modern cloud data platforms such as Snowflake, Databricks, Amazon Redshift, Google ...

Data Engineer

Richmond, VA · Remote

$50 - $87/hr

Join a fully remote opportunity where you'll help shape data-driven reporting, streamline workflows ... This role blends hands-on data engineering with dashboard development, offering the chance to work ...

Data Engineer

Chantilly, VA · On-site +1

$62K - $141K/yr

Remote Work: No Job Number: R0248636 Location: Chantilly,VA,US Share job via: Share Data Engineer The Opportunity: Booz Allen is seeking a Data Engineer to architect, develop, and optimize scalable ...

ETL Data Engineer

Mclean, VA · On-site +1

$62K - $141K/yr

Remote Work: No Job Number: R0241379 Location: McLean,VA,US Share job via: Share ETL Data Engineer The Opportunity: As a data engineer, you know that a good site or system needs the right combination ...

Senior Data Engineer

VA · Remote

$140K/yr

We are seeking a Senior Data Engineer to design, develop, and scale the data platform that powers ... This is a full-time, salaried, remote position. Candidate must reside within the Continental U.S.

Mission (Data) Engineer

Arlington, VA · Remote

$131K - $158K/yr

Mission (Data)Engineer Travel: Approximately 10% international travel required. Number of Openings ... Flexible remote work environment * Additional benefits like flexible hours, work travel ...

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 ...

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 ...

Sr. Staff Data Engineer

Richmond, VA · On-site +1

$104K - $142K/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 ...

This is a Remote position. Key Responsibilities * Data Ingestion and Integration: * Design and ... Integrate data engineering workflows with existing software systems and platforms. * Monitoring and ...

Showing results 21-40

Remote Amazon Data Engineer information

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 Virginia?

The most popular types of Amazon Data Engineer jobs in Virginia are:

What job categories do people searching Remote Amazon Data Engineer jobs in Virginia look for?

The top searched job categories for Remote Amazon Data Engineer jobs in Virginia are:

What cities in Virginia are hiring for Remote Amazon Data Engineer jobs?

Cities in Virginia with the most Remote Amazon Data Engineer job openings:

Senior Data Engineer

Mclean, VA • Remote

$107K - $145K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 18 days ago


Job description

Senior Data Engineer

Job Number: 912

This is a remote position.

Ad Hoc is a technology company that empowers organizations to deliver scalable, impactful digital services. Using modern, agile methods, our team creates products that meet people’s needs and transform their experience of government.

Work on things that matter

Our collaborations have shaped some of the defining moments in public-sector service delivery. We’ve helped build products that connect Veterans to tailored services, help millions access affordable health care, and support important programs like Head Start. As we work with agencies to deliver critical services, we’re also changing how the government approaches technology.

Built for a remote life

Our culture, communications, and tools are built for remote work, enabling us to bring together top talent nationwide. At Ad Hoc, remote life empowers our teams to design work environments that fit their lives and that foster flexibility and collaboration to achieve positive outcomes for our customers.

Committed to high expectations and a welcoming culture

Ad Hoc values acceptance, accountability, and humility. We aren’t heroes. We learn from our mistakes and improve the process for the next time. We build small, inclusive teams to collaborate closely with our partners to solve the right problems and deliver software that works.

The Federal Civilian business unit supports many customers spanning the federal, commercial, and nonprofit space. Our customers include NASA, the General Services Administration, Office of Personnel Management, the Library of Congress, Health & Human Services, and the FDIC. We partner with these agencies to build new capabilities, deliver products, establish data as a strategic asset for informed decision-making, modernize legacy systems, and build the digital service infrastructure necessary to scale their mission impact.

Primary Responsibilities

Senior Data Engineer serves as an experienced individual contributor within a team, with the expectation that you will continue to develop your leadership, technical guidance, and mentoring skills. With minimal oversight from leadership, you will design, build, and optimize scalable data solutions that support business and customer needs while ensuring projects meet scope, schedule, and delivery commitments.

As a Senior Data Engineer, you will contribute to the long-term data strategy of the program, influence architectural decisions, and collaborate closely with software engineers, product managers, analysts, architects, and stakeholders to deliver reliable, secure, and scalable data platforms. You may serve as the primary data engineering lead for initiatives and utilize strong leadership and communication skills to drive improvements in data engineering processes, platform reliability, and engineering best practices.

Primary expectations of a Senior Data Engineer include:

  • Evaluate and recommend multiple technical approaches to solve complex data engineering and architecture challenges.
  • Design, develop, maintain, and optimize scalable data pipelines supporting both batch and real-time processing.
  • Design and implement robust ETL/ELT workflows that transform raw data into reliable, consumable datasets.
  • Build and maintain scalable data models, data warehouses, and cloud-native data architectures.
  • Develop solutions for structured, semi-structured, and unstructured data sources.
  • Generate data architecture recommendations and successfully implement approved solutions.
  • Ensure data quality, integrity, governance, lineage, security, and observability across data platforms.
  • Optimize database performance, query execution, storage strategies, and overall system scalability.
  • Diagnose and resolve production issues while implementing long-term improvements to increase system reliability and performance.
  • Collaborate with cross-functional teams to translate business requirements into scalable technical solutions.
  • Present technical designs, architecture diagrams, and implementation strategies to clients, stakeholders, partners, and engineering teams.
  • Champion data engineering best practices, coding standards, automation, and operational excellence.
  • Mentor junior engineers through technical guidance, code reviews, design discussions, and knowledge sharing.
  • Lead small projects or serve as the technical lead for data engineering initiatives when needed.
  • Effectively communicate technical challenges, risks, and progress with engineering teams, leadership, clients, and stakeholders.
  • Participate in technical interviews and contribute to hiring decisions.


Required Qualifications & Technical Skills

  • Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical discipline with 7+ years of professional experience. Relevant years of experience may be substituted for formal education.
  • 7+ years of experience designing, building, and maintaining enterprise-scale data platforms and data pipelines.
  • Strong proficiency in SQL with experience developing, optimizing, and troubleshooting complex queries and large datasets.
  • Professional experience developing software and data solutions using Python, Java, Scala, or a comparable programming language.
  • Experience designing, developing, and maintaining ETL/ELT pipelines for batch and real-time data processing.
  • Experience working with cloud-based data platforms and services within AWS, Microsoft Azure, or Google Cloud Platform.
  • Experience with modern cloud data platforms such as Snowflake, Databricks, Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.
  • Experience with relational database technologies such as PostgreSQL, SQL Server, Oracle, or MySQL, along with familiarity with NoSQL database solutions.
  • Experience with distributed data processing frameworks such as Apache Spark or equivalent big data technologies.
  • Strong understanding of data modeling, dimensional modeling, schema design, data warehousing, and database optimization.
  • Experience implementing data quality, validation, governance, metadata management, and data lineage best practices.
  • Experience working with structured, semi-structured, and unstructured data from multiple sources.
  • Experience with version control systems such as Git and CI/CD practices supporting data engineering workflows.
  • Understanding of data security, privacy, encryption, and access control principles.
  • Experience monitoring, troubleshooting, and optimizing production data systems for scalability, availability, and performance.
  • Experience working within Agile software development environments and collaborating across cross-functional engineering teams.
  • Strong analytical, troubleshooting, and problem-solving skills with the ability to make sound technical decisions.
  • Excellent written and verbal communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
  • Demonstrated ability to mentor junior engineers through code reviews, technical guidance, and knowledge sharing.
  • Ability to obtain and maintain a U.S. Public Trust clearance.


Preferred Qualifications

  • Experience supporting U.S. Federal Government programs or other highly regulated environments.
  • Experience with orchestration platforms such as Apache Airflow, Prefect, Azure Data Factory, or AWS Step Functions.
  • Experience with streaming technologies such as Apache Kafka, Amazon Kinesis, or Azure Event Hubs.
  • Experience using dbt or other modern data transformation frameworks.
  • Experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation.
  • Experience working with Docker and Kubernetes in cloud-native environments.
  • Experience building analytics and business intelligence solutions using Tableau, Power BI, Looker, or similar visualization tools.
  • Existing Public Trust or higher security clearance.
  • Experience serving as a technical lead or mentoring engineers on enterprise-scale data initiatives.

To learn more about working at Ad Hoc, please visit:https://adhocteam.us/join

Benefits:

  • Company-subsidized health, dental, and vision insurance

  • Flexible PTO

  • 401K with employer match

  • Paid parental leave after one year of service

  • Employee Assistance Program

Ad Hoc LLC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, ancestry, sex, sexual orientation, gender identity or expression, religion, age, pregnancy, disability, work-related injury, covered veteran status, political ideology, marital status, or any other factor that the law protects from employment discrimination.

We value the unique skills gained through military service and encourage veterans and transitioning service members to apply.

In support of various state and city equal pay transparency laws, Ad Hoc job descriptions feature the starting range we reasonably expect to pay to candidates who would join our team with little to no need for training on the responsibilities we've outlined above. Actual compensation is influenced by a wide range of factors including but not limited to skill set, level of experience, and responsibility. The range of starting pay for this role is $130,000-$140,000. Our recruiters will be happy to answer any questions you may have, and we look forward to learning more about your salary requirements.

job reference:

https://adhoc.team/