We 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