Senior Python Data Engineer
Role Overview
Senior Python Data Engineer focused on scalable data connectors, backend development, and integration pipelines.
The posting states 6–10 years of experience, full-time employment, and a role location across Persistent locations.
Key Skills for This Role
Full Job Posting
Position
Senior Python Data Engineer focused on scalable data connectors, backend development, and integration pipelines.
The posting states 6–10 years of experience, full-time employment, and a role location across Persistent locations.
What you'll do
- Build reusable connectors for CRM, advertising, POS, client systems, and third-party APIs.
- Develop reliable ingestion pipelines and integration frameworks; own connector development through maintenance.
- Implement API integrations using REST, OAuth, API keys, pagination, and rate limiting.
- Manage schema evolution, mapping, transformation, and backward compatibility.
- Design ETL/ELT pipelines for large data volumes.
- Provide production logging, monitoring, alerting, observability, and operational dashboards.
- Coordinate client data onboarding with product, data strategy, client technical, and business teams.
- Resolve complex integration issues and improve reliability, scalability, performance, and operational efficiency.
- Apply security, automation, documentation, testing, and code-quality practices; support architecture, modernization, and production operations.
Expertise you'll bring
- 6–10 years in data engineering, backend development, and data integration projects.
- Strong hands-on Python and backend engineering expertise.
- Experience with REST APIs, OAuth, API key management, pagination, and rate limiting.
- Experience building enterprise data connectors and integration platforms; expertise in ETL/ELT, ingestion frameworks, and data processing.
- Strong SQL skills for validation, transformation, optimization, and troubleshooting.
- Experience with orchestration platforms such as Apache Airflow, dbt, or similar.
- Understanding of connector lifecycle management, Git, schema evolution, metadata, data mapping, and backward compatibility.
- Experience with Datadog, ELK Stack, Grafana, or similar observability and monitoring tools.
- Hands-on Docker and containerized deployment experience.
- Strong analysis, troubleshooting, root-cause analysis, communication, stakeholder management, and documentation skills; ownership and ability to deliver integrations on schedule.
Benefits
- Competitive salary and benefits package, quarterly growth opportunities, and company-sponsored education and certifications.
- Flexible work hours, employee engagement initiatives, annual health check-ups, and insurance coverage for employees and eligible family members.
Workplace
- The description states that Persistent supports hybrid work and flexible hours.
About Persistent
Persistent describes itself as an AI-led, platform-driven digital engineering and enterprise modernization partner serving organizations across industries.
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