Senior Data Engineer

TL;DR

Senior Data Engineer (ETL/ELT, Python/SQL): Design, implement, and maintain enterprise-grade ETL/ELT pipelines and build analysis-ready data models, warehouses, and Lakehouse environments with an accent on data architecture, infrastructure optimization, and secure, scalable data governance. Focus on monitoring and improving pipeline performance, ingesting and transforming large-scale datasets from APIs and relational/unstructured sources, and enabling reliable analytics for senior leadership decisions.

Company

hirify.global provides strategic consulting, program management, and data-driven analytics to federal public health agencies.

What you will do

• Design, implement, and maintain enterprise-grade ETL/ELT pipelines using Python and SQL.
• Build and optimize data models, warehouses, and Lakehouse environments (e.g., Databricks).
• Ingest, clean, validate, and transform large-scale datasets from APIs, relational sources, and unstructured systems.
• Implement data quality, metadata management, and governance controls for trustworthy analytics workflows.
• Collaborate with cloud engineering teams to deploy and manage data solutions on Azure.
• Monitor, troubleshoot, and improve pipeline performance using logging, alerting, and CI/CD practices; document architecture and operational procedures.

Requirements

• 8+ years of experience in data engineering, software engineering, or database architecture.
• 6+ years of experience with Python and SQL building scalable ETL/ELT pipelines.
• 2+ years with cloud data ecosystems such as Azure Data Factory.
• 1+ years with modern data processing frameworks such as Databricks.
• Must be a US Citizen and be able to obtain a US Government security clearance (Public Trust 5) within a reasonable period.
• Knowledge of data governance, security, and compliance principles for enterprise data environments.

Culture & Benefits

• Medical, Dental, Vision, and Life Insurance.
• Long and Short-Term Disability Insurance.
• Paid Time Off (PTO) and paid holidays.
• 401K with company match.
• Growth and promotion opportunities.

Hiring process

• Interviews to assess technical fit for data engineering, pipelines, and data governance.
• Security clearance eligibility review as part of the hiring process.

Location: DC Metro area, Washington, DC, USA