Senior Data Engineer
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Before you apply
SalaryNo pay range posted
LocationWashington, District of Columbia, United States
Work moderemote
Typefull-time
SenioritySenior
Experience5+ yrs
DepartmentFederal
Company size51–200 people
PostedJul 30, 2026 · 3mo ago
Verified live22h ago
May no longer be actively hiring
Posted by the company on Jul 30, 2026No pay range listed, though District of Columbia requires one
At a glanceSummarised by Seekless from the posting.
Public Trust Clearance
Bachelor's degree in data engineering, computer science, data science, machine learning, mathematics, or a related field
5 years of applied work experience in the same fields
5 years - Maintaining SQL databases and conducting advanced operations in SQL and T-SQL
5 years - Designing, implementing, and maintaining ELT and ETL processes in cloud based data analytics environments
3 years - Working in Azure Synapse and Azure Machine Learning with the modern data stack
3 years - Manipulating data in Python
Pandas
DP-203, Microsoft Certified Azure Data Engineer Associate, or equivalent certification
Implementing pipelines and infrastructure using code first approaches: Python SDK, CLI, REST APIs, or infrastructure as code tooling such as Terraform or Bicep
Implementing source control and continuous integration and delivery workflows for data assets
Demonstrated familiarity with AI coding assistants and large language model integration patterns
PySpark or Polars at production scale
Entity resolution and attribute normalization across records with inconsistent addresses, names, and identifiers
Building self service analytic access for non engineering users
Skills
SQL
T-SQL
ELT
ETL
Azure Synapse
Azure Machine Learning
Azure Data Lake Storage
Python
Pandas
PySpark
Polars
Azure
Parquet
Terraform
Bicep
Benefits
Medical
Dental
Vision
Life insurance
Health savings account
401(k) matching
PTO
Paid holidays
Paid training
Senior Data Engineer
Location: 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 approaches and modern pipeline design patterns.
• Design, implement, and maintain the data architecture that supports products and end users, with all assets managed under source control.
• Design, implement, and maintain ELT and ETL pipelines for efficient processing of source data in Azure Synapse and Azure Machine Learning, using both SDK V1 and SDK V2.
• Migrate source data identified by SBA OIG into Azure Data Lake Storage.
• Normalize entity attributes such as addresses, phone numbers, and other common fields.
• Review, maintain, and improve existing architecture and pipelines, including periodic audits addressing bottlenecks, deprecated dependencies, and architecture drift.
• Establish quality controls across all pipelines and introduce error handling, logging mechanisms, and validation checks.
• Incorporate source control across all pipelines and analytics codebases so code can evolve iteratively without destabilizing the architecture.
• Optimize ingestion, processing, and storage across a wide variety of datasets and data types, including modern columnar formats such as Parquet.
• Develop self service capabilities that let SBA OIG analysts query and export data for investigations and audits.
• Author robust standard operating procedures governing the authoring, development, validation, publishing, execution, and monitoring of all data pipelines and assets in the Azure environment.
• Produce detailed documentation of the data architecture, including data dictionaries, entity relationship diagrams, and pipeline process maps.
• Maintain and expand the environment with additional datasets and services on request, following a defined intake and testing process before production deployment.
• Stay current with emerging AI tooling relevant to data engineering and contribute to exploratory work evaluating automation and language model assisted capabilities.
Requirements
Education
Bachelor’s degree in data engineering, computer science, data science, machine learning, mathematics, or a related field. Alternatively, five years of applied work experience in any of the same fields.
•
5 years - Maintaining SQL databases and conducting advanced operations in SQL and T-SQL.
•
5 years - Designing, implementing, and maintaining ELT and ETL processes in cloud based data analytics environments.
•
3 years - Working in Azure Synapse and Azure Machine Learning with the modern data stack. Certifications preferred, DP-203 or equivalent.
•
3 years -Manipulating data in Python. Pandas is required. PySpark and Polars preferred. Experience developing reusable, modular code preferred.
PREFERRED QUALIFICATIONS
•
DP-203, Microsoft Certified Azure Data Engineer Associate, or an equivalent current certification.
•
Implementing pipelines and infrastructure using code first approaches: Python SDK, CLI, REST APIs, or infrastructure as code tooling such as Terraform or Bicep.
•
Implementing source control and continuous integration and delivery workflows for data assets.
•
Demonstrated familiarity with AI coding assistants and large language model integration patterns.
•
PySpark or Polars at production scale.
•
Entity resolution and attribute normalization across records with inconsistent addresses, names, and identifiers.
•
Building self service analytic access for non engineering users.
Benefits
We are proud to offer competitive compensation and benefits packages to include
•
Medical
•
Dental
•
Vision
•
Basic Life
•
Health Saving Account
•
401K matching
•
Three weeks of PTO/Sick
•
11 Paid Holidays
•
Pre-Approved Online Training