Data Integration Architect - Enterprise Data Platforms

Data Engineering | ETL/ELT | SSIS | Snowflake | SQL | Data Pipelines | API Integration | Kafka | Python | Power BI | Data Quality | Cloud Data PlatformsWe are seeking a highly skilled Senior Data Engineer with strong expertise in data integration, ETL/ELT, and cloud data platforms. The ideal candidate will design and build scalable data pipelines, develop integration strategies, and ensure high-quality, reliable data movement across enterprise systems. Key Responsibilities: Define and implement data integration strategy, architecture, and roadmap (batch vs real-time, API vs ETL) Design, develop, and maintain scalable data pipelines for internal and external data sources Build and manage ETL/ELT processes using tools such as SSIS and modern data platforms Develop API-based integrations and data transformation workflows Ensure data quality through validation, cleansing, and reconciliation processes Optimize data workflows for performance, scalability, and reliability Implement monitoring, logging, error handling, and alerting mechanisms for data pipelines Maintain documentation for data flows, mappings, and transformation logic Ensure compliance with data governance, security, and regulatory standards (PII, etc.) Collaborate with business and technical stakeholders to understand data requirements and deliver solutions Required Qualifications: 7+ years of experience in Data Engineering and Data Integration Strong expertise in Data Warehousing concepts and architecture Hands-on experience with ETL/ELT tools (SSIS preferred) Strong proficiency in SQL Server or other RDBMS Experience building and maintaining data pipelines Experience implementing data quality frameworks (QA/QC) Hands-on experience with cloud data platforms (e.g., Snowflake) Experience with BI tools (e.g., Power BI) Experience with API integrations (e.g., MuleSoft) Strong communication and stakeholder management skills Preferred Qualifications: Experience with real-time data pipelines (Kafka, Python) Knowledge of Data Lakehouse architecture Experience handling sensitive data (PII, HIPAA compliance) Exposure to Salesforce integrations Familiarity with AWS (Lambda), Kubernetes, or containerization tools Experience with Microsoft 365 and MS Access