Title: Senior Data Engineer
Work location: Remote
Agency: Small Business Administration (SBA)
Duration of contract: 5 years
Job Responsibilities:
- Design, implement, and maintain ELT/ETL pipelines for efficient processing of source data in Azure Synapse and Azure Machine Learning (using SDK V1 and SDK V2)
- Review, maintain, and improve existing architecture and pipelines, including periodic audits to address bottlenecks, deprecated dependencies, and architecture drift.
- Establish quality controls for maintaining all pipelines, and introduce error handling, logging mechanisms, and validation checks.
- Incorporate source control for all pipelines and data analytics codebases to enable iterative code development while ensuring data architecture stability.
- Optimize the ingestion, processing, and storage of a wide variety of datasets and data types, including modern columnar formats such as Parquet.
- Design, implement, and maintain an efficient, secure, stable, and flexible data architecture that supports products and end-users, with all assets managed via source control.
- Develop self-service capabilities for analysts to query and export data for investigations and audits.
- Coordinate with data scientists to ensure the architecture efficiently supports machine learning algorithms and data pipelines in Azure Machine Learning.
- Assist with data products by providing highly skilled and authoritative expertise on data engineering methods and best practices, including code-first development approaches and modern pipeline design patterns.
- Develop robust standard operating protocols (SOPs) dictating the authoring, development, validation, publishing, execution, and monitoring of all data pipelines and assets in Azure environment.
- Provide detailed documentation of the data architecture, including data dictionaries, ER diagrams, and pipeline process maps.
- Maintain and expand the environment with additional datasets and services upon request, following a defined intake and testing process prior to production deployment.
- Stay current with emerging AI tools relevant to data engineering, and contribute to exploratory efforts evaluating automation and LLM-assisted capabilities.
Requirements:
- Five (5) years of hands-on experience in each of the following:
a. Maintaining SQL databases and conducting advanced operations in SQL and T-SQL.
b. Designing, implementing, and maintaining ELT/ETL processes in cloud-based data analytics environments.
2. Three (3) years of hands-on experience in each of the following:
A. Working in Azure Synapse and Azure Machine Learning, with the modern data stack. Certifications preferred (DP-203 or equivalent).
B. Manipulating data in Python. Pandas required. PySpark/Polars preferred. Experience developing reusable, modular code preferred.
Preferred experience:
- Implementing pipelines and infrastructure using code-first approaches (Python SDK, CLI, REST APIs, or IaC tooling)
- Implementing source control and CI/CD workflows
- Demonstrated familiarity with AI coding assistants and LLM integration patterns
Benefits:
- Base salary based on job, experience and skill level.
- Health benefits include medical, dental, and vision plans.
- 401(k) with 4% company match.
- 10 days Paid time off (PTO) and eleven (11) paid federal holidays.
Pay: $80,000.00 - $90,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Health insurance
- Paid time off
Application Question(s):
- What is your work status: US Citizen, Permanent resident, H1B, OPT?
- Do you currently hold an active security clearance?
- What is your expected annual salary?
Education:
Work Location: Remote
