Data Engineer | Req#4498
Remote, United States
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- Salary not listed in the saved posting
- Work setup
Working pattern needs review — work setup source
ActioNet has an exciting opportunity for a Data Engineer to join our interdisciplinary team to deliver the next generation of advanced data analytics and production systems for one of the nation’s leading sources of demographic, economic, and statistical data products. The Data Engineer will collaborate with software engineering, DevOps, data science, and product management teams to design/build solutions that transform legacy on-premises systems to new highly scalable cloud-native architectures for pipelines to dynamically extract, transform, and load (ETL) complex data from various sources into accessible formats for a wide range of analysis and reporting needs. This role demands expertise in Python and involves building complex pipelines from scratch, managing data flow within the AWS ecosystem, and conducting rigorous testing to ensure accuracy and completeness, consistency, and quality of all outputs. This position is Hybrid - with on-site support in Suitland, MD and REMOTE. Federal position requires Public Trust. Candidates must be US Citizens to be eligible.
Listed location: Remote, United States
Read the full posting- Employment
- Unconfirmed
What you’ll work on
Full postingCollaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver tailored data solutions.
Develop efficient data processing and transformation workflows to support analytics and reporting needs.
Implement processes for data cleaning, transformation, and validation to ensure data accuracy, consistency, and compliance with security and privacy policies.
From the employer’s posting
Responsibilities: Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver tailored data solutions. Develop efficient data processing and transformation workflows to support analytics and reporting needs.
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver tailored data solutions. Develop efficient data processing and transformation workflows to support analytics and reporting needs. Design, build, and maintain data pipelines and automated extract, transform, load (ETL) processes using tools like Python, R, and platform‑specific environments such as Jupyter Notebooks.
Integrate disparate structured and unstructured data from APIs, databases, and cloud storage into unified datasets utilizing ETL patterns, frameworks, query techniques. Implement processes for data cleaning, transformation, and validation to ensure data accuracy, consistency, and compliance with security and privacy policies. Develop dashboards, visualizations, and analytical products leveraging QuickSight or other mission‑approved tools to support operational decision‑making.
What you’ll bring
All qualificationsCore experience
- 5+ years of experience as a Data Engineer, Data Scientist, or Backend Software Engineer
- Bachelor’s degree from an accredited college or university with a major in computer science, statistics, mathematics, economics, or related field
- Proficient in handling large-scale data projects involving data integration, cleaning, ETL, analysis, aggregation, tabulation, and reporting
- Experience developing and implementing data reliability, efficiency, and qualify checks and processes
- Experience leveraging AWS services (e.g., S3, EMR, Glue, Lambda, Athena, Redshift, SageMaker, QuickSight) to build and deploy data solutions in a cloud-native environment.
- Experience with structured and unstructured data databases including Oracle, PostGreSQL, MySQL, Athena, Redshift, MongoDB etc.
Preferred experience
- Experience with SAS highly preferred
- Experience with data platforms like Cube, Athena, Redshift, Apache Spark, Databricks, Palantir, Snowflake, Google BigQuery
- Experience with AWS BI and AI/ML services including QuickSight, SPICE, SageMaker etc.
- Experience with workflow orchestration tools e.g.
Qualification wording
5+ years of experience as a Data Engineer, Data Scientist, or Backend Software Engineer
Bachelor’s degree from an accredited college or university with a major in computer science, statistics, mathematics, economics, or related field
Proficient in handling large-scale data projects involving data integration, cleaning, ETL, analysis, aggregation, tabulation, and reporting
Experience developing and implementing data reliability, efficiency, and qualify checks and processes
Experience leveraging AWS services (e.g., S3, EMR, Glue, Lambda, Athena, Redshift, SageMaker, QuickSight) to build and deploy data solutions in a cloud-native environment.
Experience with structured and unstructured data databases including Oracle, PostGreSQL, MySQL, Athena, Redshift, MongoDB etc.
Experience with SAS highly preferred
Experience with data platforms like Cube, Athena, Redshift, Apache Spark, Databricks, Palantir, Snowflake, Google BigQuery
Experience with AWS BI and AI/ML services including QuickSight, SPICE, SageMaker etc.
Experience with workflow orchestration tools e.g. Airflow, Temporal
Tools in this posting
- Python
- R
- SAS
- SQL
- AWS
- Databricks
- Docker
- MongoDB
- MySQL
- Oracle
- PostgreSQL
- Redshift
- S3
- SageMaker
- Snowflake
- Spark
- Airflow
- Scala
- BigQuery
- Kubernetes
Source — Tool mentions in context
ActioNet has an exciting opportunity for a Data Engineer to join our interdisciplinary team to deliver the next generation of advanced data analytics and production systems for one of the nation’s leading sources of demographic, economic, and statistical data products. The Data Engineer will collaborate with software engineering, DevOps, data science, and product management teams to design/build solutions that transform legacy on-premises systems to new highly scalable cloud-native architectures for pipelines to dynamically extract, transform, and load (ETL) complex data from various sources into accessible formats for a wide range of analysis and reporting needs. This role demands expertise in Python and involves building complex pipelines from scratch, managing data flow within the AWS ecosystem, and conducting rigorous testing to ensure accuracy and completeness, consistency, and quality of all outputs. This position is Hybrid - with on-site support in Suitland, MD and REMOTE.
- Develop efficient data processing and transformation workflows to support analytics and reporting needs. - Design, build, and maintain data pipelines and automated extract, transform, load (ETL) processes using tools like Python, R, and platform‑specific environments such as Jupyter Notebooks. - Integrate disparate structured and unstructured data from APIs, databases, and cloud storage into unified datasets utilizing ETL patterns, frameworks, query techniques.
- Bachelor’s degree from an accredited college or university with a major in computer science, statistics, mathematics, economics, or related field - Strong skills in Python and SQL and proficiency with other data engineering languages (e. g., R, SAS, SCALA) - Proficient in handling large-scale data projects involving data integration, cleaning, ETL, analysis, aggregation, tabulation, and reporting
Preferred Qualifications: - Experience with SAS highly preferred - Experience with data platforms like Cube, Athena, Redshift, Apache Spark, Databricks, Palantir, Snowflake, Google BigQuery
- Experience developing and implementing data reliability, efficiency, and qualify checks and processes - Experience leveraging AWS services (e.g., S3, EMR, Glue, Lambda, Athena, Redshift, SageMaker, QuickSight) to build and deploy data solutions in a cloud-native environment. - Experience with structured and unstructured data databases including Oracle, PostGreSQL, MySQL, Athena, Redshift, MongoDB etc.
- Experience with data platforms like Cube, Athena, Redshift, Apache Spark, Databricks, Palantir, Snowflake, Google BigQuery - Experience with AWS BI and AI/ML services including QuickSight, SPICE, SageMaker etc. - Experience with workflow orchestration tools e.g. Airflow, Temporal
- Experience with SAS highly preferred - Experience with data platforms like Cube, Athena, Redshift, Apache Spark, Databricks, Palantir, Snowflake, Google BigQuery - Experience with AWS BI and AI/ML services including QuickSight, SPICE, SageMaker etc.
- Experience with and interest in AI/ML and data modeling highly preferred - Experience with microservices architecture and containerization (e.g., Docker, Kubernetes) - Knowledge of DevOps practices and tools (e.g., Jenkins, GitLab CI/CD)
- Experience leveraging AWS services (e.g., S3, EMR, Glue, Lambda, Athena, Redshift, SageMaker, QuickSight) to build and deploy data solutions in a cloud-native environment. - Experience with structured and unstructured data databases including Oracle, PostGreSQL, MySQL, Athena, Redshift, MongoDB etc. - Familiarity with demographic, economic, and geospatial data sources and structures
- Experience with AWS BI and AI/ML services including QuickSight, SPICE, SageMaker etc. - Experience with workflow orchestration tools e.g. Airflow, Temporal - Familiarity with distributed high-performance computing (HPC) and parallel processing
Job description
Responsibilities:
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver tailored data solutions.
- Develop efficient data processing and transformation workflows to support analytics and reporting needs.
- Design, build, and maintain data pipelines and automated extract, transform, load (ETL) processes using tools like Python, R, and platform‑specific environments such as Jupyter Notebooks.
- Integrate disparate structured and unstructured data from APIs, databases, and cloud storage into unified datasets utilizing ETL patterns, frameworks, query techniques.
- Implement processes for data cleaning, transformation, and validation to ensure data accuracy, consistency, and compliance with security and privacy policies.
- Develop dashboards, visualizations, and analytical products leveraging QuickSight or other mission‑approved tools to support operational decision‑making.
- Provide full lifecycle assistance in deploying, optimizing, maintaining complex code with data processing routines running in development, test, and production
- Optimize code through advanced algorithmic concepts to facilitate more efficient
- 5+ years of experience as a Data Engineer, Data Scientist, or Backend Software Engineer
- Bachelor’s degree from an accredited college or university with a major in computer science, statistics, mathematics, economics, or related field
- Strong skills in Python and SQL and proficiency with other data engineering languages (e. g., R, SAS, SCALA)
- Proficient in handling large-scale data projects involving data integration, cleaning, ETL, analysis, aggregation, tabulation, and reporting
- Experience developing and implementing data reliability, efficiency, and qualify checks and processes
- Experience leveraging AWS services (e.g., S3, EMR, Glue, Lambda, Athena, Redshift, SageMaker, QuickSight) to build and deploy data solutions in a cloud-native environment.
- Experience with structured and unstructured data databases including Oracle, PostGreSQL, MySQL, Athena, Redshift, MongoDB etc.
- Familiarity with demographic, economic, and geospatial data sources and structures
- Experience working in an Agile organization using Scrum, Kanban, Jira, Confluence, and SAFe.
- Excellent communication and teamwork skills
- Strong skills preparing and presenting design/architectural documents to clients
- Requires a Public Trust - must be US Citizen to be eligible.
- Experience with SAS highly preferred
- Experience with data platforms like Cube, Athena, Redshift, Apache Spark, Databricks, Palantir, Snowflake, Google BigQuery
- Experience with AWS BI and AI/ML services including QuickSight, SPICE, SageMaker etc.
- Experience with workflow orchestration tools e.g. Airflow, Temporal
- Familiarity with distributed high-performance computing (HPC) and parallel processing
- Experience with and interest in AI/ML and data modeling highly preferred
- Experience with microservices architecture and containerization (e.g., Docker, Kubernetes)
- Knowledge of DevOps practices and tools (e.g., Jenkins, GitLab CI/CD)
- Familiarity with agile development methodologies and version control systems (e.g., GitHub, Bitbucket)
- Advanced and Managed IT Services
- Agile Software Development
- DevSecOps
- Cybersecurity
- Health IT
- C4ISR & SIGINT
- Data Center Engineering & Operations
- Engineering & Installation
- Commitment to Employees: We are committed to making ActioNet a great place to work and continue to invest in our ActioNeters.
- Commitment to Customers: We are committed to our customers by driving and sustaining Service Delivery Excellence.
- Commitment to Community: We are committed to giving back to our community, helping others, and making the world a better place for our next generation.
- Medical Insurance
- Vision Insurance
- Dental Insurance
- Life and AD&D Insurance
- 401(k) Savings Plan
- Education and Professional Training
- Flexible Spending Accounts (FSA)
- Employee Referral and Merit Recognition Programs
- Employee Assistance and Identity Theft Protection
- Paid Holidays: 11 per year
- Paid Time Off (PTO)
- Disability Insurance
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Remote, United States
ActioNet has an exciting opportunity for a Data Engineer to join our interdisciplinary team to deliver the next generation of advanced data analytics and production systems for one of the nation’s leading sources of demographic, economic, and statistical data products. The Data Engineer will collaborate with software engineering, DevOps, data science, and product management teams to design/build solutions that transform legacy on-premises systems to new highly scalable cloud-native architectures for pipelines to dynamically extract, transform, and load (ETL) complex data from various sources into accessible formats for a wide range of analysis and reporting needs. This role demands expertise in Python and involves building complex pipelines from scratch, managing data flow within the AWS ecosystem, and conducting rigorous testing to ensure accuracy and completeness, consistency, and quality of all outputs. This position is Hybrid - with on-site support in Suitland, MD and REMOTE. Federal position requires Public Trust. Candidates must be US Citizens to be eligible.
- Work authorization
This position is Hybrid - with on-site support in Suitland, MD and REMOTE. Federal position requires Public Trust. Candidates must be US Citizens to be eligible. Responsibilities:
More source context
- Strong skills preparing and presenting design/architectural documents to clients - Requires a Public Trust - must be US Citizen to be eligible. Preferred Qualifications:
- Status in our records
- Active
- First seen by us
- Apr 30, 2026
- Recorded sightings
- 51
- Last seen by us
- Oct 15, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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