Direct Hire Authority Dha Jobs in Washington DC

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EASE Product Manager, Shopping (Remote-Eligible)

Company: Capital One

Location: Washington DC

Posted Jan 26, 2025

Capital One is seeking a Product Manager for their growing team in Capital One Shopping. The ideal candidate should have a strong background in data analysis, SQL, and emerging technologies. They should be comfortable working with backend products, have a customer-first mindset, and be a strategic thought leader. The role involves leading teams of software and data engineers, understanding enterprise data requirements, and creating a vision and roadmap for the product. The minimum annual salary for this role is $144,000 for remote positions and ranges up to $197,200 for on-site positions in New York City and San Francisco.

Frequently Asked Questions

What are typical salary ranges by seniority for Direct Hire Authority DHA roles?
Entry‑level (0–2 years): $70,000–$90,000. Mid‑level (3–5 years): $90,000–$120,000. Senior (6+ years): $120,000–$160,000. Lead/Manager: $160,000–$200,000.
What skills and certifications are required for Direct Hire Authority DHA positions?
Must‑have skills: Python, SQL, Airflow, dbt, Snowflake, Kubernetes, Terraform. Certifications: AWS Certified Big Data – Specialty, Google Cloud Professional Data Engineer, Snowflake SnowPro Core, Databricks Certified Data Engineer Associate.
Is remote work available for Direct Hire Authority DHA roles?
Approximately 85% of DHA listings offer fully remote or hybrid options. Remote roles typically require 9‑5 UTC+0 alignment, flexible hours, and proficiency with collaboration tools like Slack, Teams, and GitHub.
What are common career progression paths within Direct Hire Authority DHA?
Data Engineer → Senior Data Engineer → Lead Data Engineer → Data Ops Manager → Director of Data Operations. Each step adds responsibilities in architecture, team leadership, and strategic data governance.
What industry trends are shaping Direct Hire Authority DHA roles?
Growing adoption of serverless data warehouses (Snowflake, BigQuery), real‑time streaming (Kafka, Pulsar), AI‑driven data catalogs, increased focus on data privacy (GDPR, CCPA), and demand for cross‑functional data science integration.

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