Sr Data Integration Engineer

The Sr. Data Integration Engineer will lead the design, development, and implementation of scalable data solutions, including a Customer Data Platform (CDP) and associated API frameworks. This role is critical in building a unified, secure, and high-performing data ecosystem that supports customer insights, personalization, analytics, and enterprise-wide data integration. Job Duties and Responsibilities (Essential Job Functions) Common job activities are listed below; actual position responsibilities may vary. Refer to your manager or human resources for specific duties and performance expectations. 1. Data Engineering & Integration Develop and maintain scalable data pipelines and workflows using Python and modern data tools. Build and maintain production-grade data integrations across internal and third-party systems. Code, test, deploy, orchestrate, monitor, document, and troubleshoot cloud-based data engineering processes and associated automation in accordance with best practices and security standards throughout the development lifecycle. Design and implement a robust, scalable Customer Data Platform (CDP) to centralize and unify customer data from multiple sources (CRM, ERP, web, mobile, etc.). Develop and maintain APIs and data pipelines to support real-time and batch data integration between the CDP and internal/external systems. 2. Optimization & Performance Optimize and manage data environments, including data modeling, security practices, and Lakehouse performance. Monitor and optimize data flows and API performance to ensure high availability and low latency. Troubleshoot and resolve data-related issues, ensuring system reliability and efficiency. 3. Collaboration & Communication Collaborate with cross-functional teams including marketing, product, engineering, and business stakeholders to define data requirements and integration strategies. Communicate effectively with stakeholders, translating technical concepts into actionable insights. 4. Governance & Compliance Implement data governance and privacy practices to ensure compliance with regulations (e.g., GDPR, CCPA). Ensure data quality, governance, and compliance with internal policies and external regulations. 5. Tools & Automation Utilize Git version control and CI/CD pipelines to deploy and manage data workflows. Evaluate and recommend tools, platforms, and technologies to support the CDP and integration framework. Document architecture, data flows, and integration patterns to support maintainability and scalability. 6. Perform other duties as requested or as needed to fulfill the purpose of the job. Performance Expectations Meet all performance and behavior expectations outlined in the company performance appraisal form or communicated by management. Perform responsibilities as directed achieving desired results within expected time frames and with a high degree of quality and professionalism. Establish and maintain positive and productive work relationships with all staff, customers and business partners. Demonstrate the behavioral and technical competencies necessary to effectively complete job responsibilities. Take personal initiative for technical and professional development. Follow the company HR Policy, the Code of Business Conduct and all subsidiary and department policies and procedures, including protecting confidential company information, attending work punctually and regularly, and following good safety practices in all activities. Qualifications Education: Bachelor’s or Master’s degree in computer science, engineering, or related field. Experience: 10+ years of experience with RESTful APIs. 10+ years of experience with SQL, Python, or PowerShell. 5+ years of experience with cloud platforms such as Azure, AWS, GCP, ect. 5+ years of experience with cloud-native tools (ADF, Glue, Cloud Data Fusion, dbt, Airflow). Proven experience building or integrating with Customer Data Platforms such as Segment, Salesforce CDP, Adobe Experience Platform, or custom-built solutions. Experience with data integration tools such as Apache NiFi, Talend, Informatica, etc. Experience with identity resolution, customer segmentation, and real-time personalization use cases preferred. Knowledge and Skills: Strong proficiency in ETL/ELT pipelines and data modeling. Familiarity with event-driven architectures, message queues (ex., Kafka), and microservices. Strong understanding of data privacy and security best practices. Familiarity with CI/CD pipelines and Infrastructure as Code (IaC) tools (Bicep, Terraform, Pulumi, CloudFormation) Knowledge of data warehousing and analytics platorms (ex. Snowflake, BigQuery, Databricks) preferred. Wage: $153,000 - $178,000 annually; actual wage is based upon education and experience. Potential for annual discretionary bonus. Benefits: Full suite of benefits including Medical, Health Savings Account, Dental, Vision, Life Insurance, Paid Vacation (PTO), 401(k) with employer match, Flexible Spending Account, and Employee Assistance Program (EAP) Equal Opportunity Employer