Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,229 postings in the last year. Stated ranges, not salaries paid.
Data Engineer
Arlington, VA, 22202, US
Live, first seen by us 24 days ago- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
- Not stated
- Employment
Contract — employment source
Employment type in the employer’s posting: CONTRACTOR
From the employer’s posting
What you’ll work on
Full postingArchitect, develop, and optimize data ingestion and transformation pipelines
Maintain streaming and analytical pipelines in Databricks Lakehouse environments
Collaborate with federal technical teams and platform, SRE, and governance staff
From the employer’s posting
architecting, developing, optimizing, and maintaining high‑performance data ingestion, transformation, streaming, and analytical pipelines
within Databricks‑enabled Lakehouse environments
This role is expected to collaborate closely with the federal technical teams, and cross‑task platform, SRE, governance, privacy, and development personnel.
What you’ll bring
All qualificationsCore experience
- Ability to obtain and maintain a Public Trust clearance
- Databricks Data Engineer Associate Certification
- Bachelor's degree in a related field, or 4+ years of equivalent experience
Qualification wording
Ability to obtain and maintain a Public Trust clearance.
Databricks Data Engineer Associate Certification.
Bachelor's degree in computer science, information systems, engineering, or related field; or four (4) or more years of equivalent experience within the last six (6) years in lieu of a degree.
Education & alternatives
- Eight (8) or more years of experience (2 of which must be within the last five (5) years) in data engineering, ETL/ELT development, or distributed data processing within cloud environments or platforms (e.g. AWS, Azure, GCP, Snowflake, Databricks, etc.). - Bachelor's degree in computer science, information systems, engineering, or related field; or four (4) or more years of equivalent experience within the last six (6) years in lieu of a degree. - Databricks Data Engineer Associate Certification.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 17, 202624 days ago
- Recorded sightings
- 29
- Last seen by us
- Nov 10, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 24
Similar jobs usually come down between day 6 and day 55.
At SiloSmashers, jobs usually come down by about day 130.
From 12,966 similar postings that came down, and 10 of SiloSmashers’s. Coming down is not always a hire.
SiloSmashers is hiring
9 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring is picking up
- Its jobs tend to stay up a long time
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- Databricks
- Delta Lake
- GCP
- Snowflake
- Terraform
- PySpark
Where the posting names them
- Hands on experience with Databricks Workflows/Jobs, Auto Loader, COPY INTO, Structured Streaming, and introductory Databricks SQL Warehouse usage. Understanding of common performance considerations (e.g., cluster sizing, partitioning, basic caching strategies). - Practical experience building batch or streaming pipelines using Python and PySpark, along with cloud-native services in AWS or Microsoft Azure. - Experience implementing secure cloud data integrations or platform configurations such as external locations, storage credentials, secret scopes, or identity federation basics.
- Foundational experience designing and implementing Databricks Lakehouse solutions, including: Basic Delta Lake table design, schema evolution, and familiarity with medallion architecture (bronze/silver/gold). - Hands on experience with Databricks Workflows/Jobs, Auto Loader, COPY INTO, Structured Streaming, and introductory Databricks SQL Warehouse usage. Understanding of common performance considerations (e.g., cluster sizing, partitioning, basic caching strategies). - Practical experience building batch or streaming pipelines using Python and PySpark, along with cloud-native services in AWS or Microsoft Azure.
- Ability to obtain and maintain a Public Trust clearance. - Eight (8) or more years of experience (2 of which must be within the last five (5) years) in data engineering, ETL/ELT development, or distributed data processing within cloud environments or platforms (e.g. AWS, Azure, GCP, Snowflake, Databricks, etc.). - Bachelor's degree in computer science, information systems, engineering, or related field; or four (4) or more years of equivalent experience within the last six (6) years in lieu of a degree.
- Databricks Data Engineer Associate Certification. - At least one foundational cloud certification (e.g., AWS Cloud Practitioner, AWS Developer Associate, Azure Fundamentals, or equivalent). - Preferred but not required: Databricks Lakehouse Architect, Generative AI Associate/Professional, or related ML/AI certifications.
- Experience implementing secure cloud data integrations or platform configurations such as external locations, storage credentials, secret scopes, or identity federation basics. - Experience working with Git-based workflows and CI/CD tooling (e.g., GitHub Actions, Azure DevOps), plus familiarity with Databricks Repos, Asset Bundles, or basic Terraform/IaC concepts. - Introductory experience or interest in AI/ML enabled engineering, such as Databricks Model Serving, Genie, Agent Bricks, or equivalent cloud-native ML platforms.
Position Overview SiloSmashers is hiring for a Data Engineer to support digital transformation efforts for a government customer. The selected candidate will serve as part of a team responsible for architecting, developing, optimizing, and maintaining high‑performance data ingestion, transformation, streaming, and analytical pipelines within Databricks‑enabled Lakehouse environments. This role is expected to collaborate closely with the federal technical teams, and cross‑task platform, SRE, governance, privacy, and development personnel. Required Skills
Required Skills - Foundational experience designing and implementing Databricks Lakehouse solutions, including: Basic Delta Lake table design, schema evolution, and familiarity with medallion architecture (bronze/silver/gold). - Hands on experience with Databricks Workflows/Jobs, Auto Loader, COPY INTO, Structured Streaming, and introductory Databricks SQL Warehouse usage. Understanding of common performance considerations (e.g., cluster sizing, partitioning, basic caching strategies).
- Experience working with Git-based workflows and CI/CD tooling (e.g., GitHub Actions, Azure DevOps), plus familiarity with Databricks Repos, Asset Bundles, or basic Terraform/IaC concepts. - Introductory experience or interest in AI/ML enabled engineering, such as Databricks Model Serving, Genie, Agent Bricks, or equivalent cloud-native ML platforms. Mandatory Qualifications & Requirements
- Bachelor's degree in computer science, information systems, engineering, or related field; or four (4) or more years of equivalent experience within the last six (6) years in lieu of a degree. - Databricks Data Engineer Associate Certification. - At least one foundational cloud certification (e.g., AWS Cloud Practitioner, AWS Developer Associate, Azure Fundamentals, or equivalent).
- At least one foundational cloud certification (e.g., AWS Cloud Practitioner, AWS Developer Associate, Azure Fundamentals, or equivalent). - Preferred but not required: Databricks Lakehouse Architect, Generative AI Associate/Professional, or related ML/AI certifications. - This position requires regular, physical attendance at customer sites.
Your next step
Complete your application on silosmashers.applicantpro.com. The employer’s form will show what is required.
Already applied? Track this application
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
SiloSmashers, Inc. is a leading management and IT consulting firm, serving as a trusted advisor and solutions partner to a diverse range of government, business, and not-for-profit organizations. Applying proven expertise and methodologies, we help our customers align and mobilize every aspect of their operations, strengths, and resources to achieve Peak Performance and increased business value today and through the years ahead.
Position Overview
SiloSmashers is hiring for a Data Engineer to support digital transformation efforts for a government customer. The selected candidate will serve as part of a team responsible for architecting, developing, optimizing, and maintaining high‑performance data ingestion, transformation, streaming, and analytical pipelines within Databricks‑enabled Lakehouse environments. This role is expected to collaborate closely with the federal technical teams, and cross‑task platform, SRE, governance, privacy, and development personnel.
Required Skills
- Foundational experience designing and implementing Databricks Lakehouse solutions, including: Basic Delta Lake table design, schema evolution, and familiarity with medallion architecture (bronze/silver/gold).
- Hands on experience with Databricks Workflows/Jobs, Auto Loader, COPY INTO, Structured Streaming, and introductory Databricks SQL Warehouse usage. Understanding of common performance considerations (e.g., cluster sizing, partitioning, basic caching strategies).
- Practical experience building batch or streaming pipelines using Python and PySpark, along with cloud-native services in AWS or Microsoft Azure.
- Experience implementing secure cloud data integrations or platform configurations such as external locations, storage credentials, secret scopes, or identity federation basics.
- Experience working with Git-based workflows and CI/CD tooling (e.g., GitHub Actions, Azure DevOps), plus familiarity with Databricks Repos, Asset Bundles, or basic Terraform/IaC concepts.
- Introductory experience or interest in AI/ML enabled engineering, such as Databricks Model Serving, Genie, Agent Bricks, or equivalent cloud-native ML platforms.
Mandatory Qualifications & Requirements
- Ability to obtain and maintain a Public Trust clearance.
- Eight (8) or more years of experience (2 of which must be within the last five (5) years) in data engineering, ETL/ELT development, or distributed data processing within cloud environments or platforms (e.g. AWS, Azure, GCP, Snowflake, Databricks, etc.).
- Bachelor's degree in computer science, information systems, engineering, or related field; or four (4) or more years of equivalent experience within the last six (6) years in lieu of a degree.
- Databricks Data Engineer Associate Certification.
- At least one foundational cloud certification (e.g., AWS Cloud Practitioner, AWS Developer Associate, Azure Fundamentals, or equivalent).
- Preferred but not required: Databricks Lakehouse Architect, Generative AI Associate/Professional, or related ML/AI certifications.
- This position requires regular, physical attendance at customer sites.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Arlington, VA, 22202, US
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.