Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
Role: Senior Data Engineering Manager (Individual Contributor)
Location: Hybrid (Washington, DC Metro)
Type: Full-Time
About the Team:
Join a technology team responsible for delivering modern cloud-based data platforms that support enterprise analytics and business decision-making. You'll work closely with engineering and business partners to build reliable, scalable data solutions in a collaborative environment.
What You'll Do:
Core Tech & Skills:
Nice to Have:
Why It's Great:
Location: Hybrid (Washington, DC Metro)
Type: Full-Time
About the Team:
Join a technology team responsible for delivering modern cloud-based data platforms that support enterprise analytics and business decision-making. You'll work closely with engineering and business partners to build reliable, scalable data solutions in a collaborative environment.
What You'll Do:
- Lead the design, maintenance, and optimization of a modern cloud data platform.
- Build and support scalable data pipelines, orchestration workflows, and automated data processing.
- Develop high-quality data models and transformation frameworks for reporting and analytics.
- Improve platform reliability, monitoring, and operational performance across production environments.
- Partner with technical and business stakeholders to translate requirements into scalable solutions.
- Support integrations between enterprise systems, APIs, and reporting platforms.
- Mentor team members and promote engineering best practices across distributed teams.
Core Tech & Skills:
- Snowflake or Databricks
- Microsoft Azure or other major cloud platforms
- SQL
- Python
- Apache Airflow or similar workflow orchestration tools
- dbt or modern data transformation frameworks
- Power BI or enterprise BI platforms
- ETL/ELT pipeline development
- API and data integration experience
- Data modeling and warehouse architecture
Nice to Have:
- Financial services or highly regulated industry experience
- PySpark or distributed data processing
- Exposure to AI-enabled analytics or data products
- Experience working with globally distributed engineering teams
- Strong stakeholder communication and leadership skills
Why It's Great:
- Own a highly visible enterprise data platform with significant business impact.
- Work with modern cloud technologies and evolving data architecture.
- Join a collaborative engineering culture that values ownership, innovation, and continuous improvement.
Skills
SQL
ETL
Snowflake
Airflow
Apache
Azure
Continuous Improvement
Databricks
Power BI
Python
dbt
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