
Enterprise Data Architect
6 days ago
Job Overview
The role of Data Integration Specialist plays a pivotal part in designing and overseeing modern data pipelines, ensuring reliable high-performance data delivery for enterprise analytics and AI workloads.
About This Position
This key member of the internal team will lead the architecture and delivery of enterprise-scale data pipelines and integrations, enabling secure, high-quality, and scalable data flows across platforms to power analytics, BI, and AI initiatives.
Key Responsibilities
Design, build, and optimize pipelines using AWS Glue, dbt, Airflow or similar tools.
Develop scalable ETL/ELT processes in Python and SQL.
Support both batch and real-time/CDC data flows.
Manage API integrations with SaaS platforms.
Ensure seamless data movement across internal and external systems.
Implement validation, testing, and reconciliation frameworks.
Deploy monitoring, alerting, and observability tools.
Maintain data lineage, cataloging, and metadata management for compliance.
Mentor data engineering teams and champion integration standards.
Collaborate with BI, analytics, and AI teams to meet business needs.
Requirements and Expertise
Required Skills and Expertise:
Extensive experience with modern data pipeline tools (AWS Glue, dbt, Airflow, Prefect, FiveTran, or similar orchestration).
Strong proficiency in Python and SQL with experience in data transformation frameworks.
Deep knowledge of API integrations and experience with SaaS platforms.
Experience with data quality frameworks, monitoring, and alerting systems.
Knowledge of change data capture (CDC) and real-time data processing.
Understanding of data lineage, cataloging, and metadata management.
Experience with data validation, testing, and observability tools.
Desired Expertise:
Candidate should bring broad experience across a range of technologies and demonstrate the ability to rapidly evaluate, adopt, and shape new tools, frameworks, and methodologies to meet evolving business and technical needs.
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