Posted:2 days ago|
Platform:
Work from Office
Full Time
Govern data acquisition and ingestion architecture for enterprise-wide data & analytics integration.
Establish reusable, scalable, and governed interfaces to all source systems across business domains.
Oversees ingestion and integration design across 100+ data sources.
Supports 25+ data engineering and data science professionals with ingestion architecture and troubleshooting.
Main Tasks
Define ingestion frameworks for batch, streaming, and APIs.
Establish standards for JSON, CSV, XML, and unstructured data.
Collaborate with system owners to define interface specifications.
Manage schema evolution and API reliability.
Collaborate on ingestion for data science and ML pipelines
Ensure robust API and event-driven integration for AI/LLM use cases.
Review high-risk ingestion pipelines for performance and security.
Support data engineers on error handling, retries, and load orchestration.
Maintain ingestion libraries and templates.
Promote reuse and automation across engineering teams.
Maintain architectural blueprints, templates, and best practices.
Publish design guidelines and coding standards.
Monitor usage and implement auto-scaling policies.
Analyze and optimize cluster configurations for cost-efficiency.
Qualifications
Degree in Computer Science or related field; certifications in Databricks or Microsoft Azure preferred.
6-10 years in data engineering with strong focus on enterprise-scale data & analytics integration, including ML and LLM scenarios.
Experience building robust ingestion frameworks and reusable components.
Track record of architectural ownership and peer enablement with diverse teams.
Experience working in international teams across multiple time zones and cultures, preferably with teams in India, Germany, and the Philippines.
Continental
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