Sr. Data Integration Engineer

Focused on employment and labor law since 1958, Jackson Lewis P.C.’s 1,000+ attorneys located in major cities nationwide consistently identify and respond to new ways workplace law intersects business. We help employers develop proactive strategies, strong policies and business-oriented solutions to cultivate high-functioning workforces that are engaged and stable, and share our clients’ goals to emphasize belonging and respect for the contributions of every employee.

The Firm is ranked in the First Tier nationally in the category of Labor and Employment Litigation, as well as in both Employment Law and Labor Law on behalf of Management, in the U.S. News - Best Lawyers® “Best Law Firms”. 

We seek a Senior Data Integration Engineer who will report directly to the Data Integration and Data Warehouse Manager and play a critical role in building and optimizing the firm’s data integration pipelines. The ideal candidate will have deep hands-on expertise in designing, building, and managing complex data integration workflows, with a strong focus on tools like Boomi, Matillion, and other modern data integration platforms. The role requires expertise in API integration, Change Data Capture (CDC), batch processing, delta processing, and experience working within enterprise bus architectures to ensure seamless data flow across systems. 

The Sr. Data Integration Engineer will lead the end-to-end integration process, ensuring data is accurately and efficiently moved between source systems, data warehouses, and business intelligence platforms while maintaining data quality, consistency, and timeliness. 

Key Responsibilities: 

• Data Integration Pipeline Development: 

• Design, build, and manage scalable and reliable data integration pipelines using tools like Boomi, Matillion, and Fivetran. 

• Implement and optimize ETL/ELT workflows to ensure efficient data movement between internal and external systems. 

• Develop real-time and batch integration processes that meet business requirements while ensuring data accuracy and timeliness. 
• Lead the end-to-end development of integration solutions using Boomi, support SDLC during the design process, gathering and documenting business requirements, technical requirements, data mapping, plan and execute regression, integration testing, cutover, go-live and post go-live activities.

• API and Enterprise System Integration: 

• Implement and maintain API-based integrations between various data sources and systems, including Salesforce, Workday, and Aderant. 

• Ensure seamless two-way data synchronization between SQL databases and external APIs. 

• Work closely with cross-functional teams to integrate API services into the firm’s data architecture. 

• Change Data Capture (CDC) & Delta Processing: 

• Implement and manage Change Data Capture (CDC) mechanisms across various databases (e.g., SQL, cloud databases) to track and propagate changes in real-time. 

• Develop and implement batch and delta processing strategies to optimize data flow, minimize latency, and ensure timely updates. 

• Ensure accurate and consistent data capture for historical data tracking and auditing purposes. 

• Data Quality and Governance: 

• Ensure high data quality across all integration processes, performing regular checks and validations to detect and correct any inconsistencies. 

• Collaborate with the data warehouse and analytics teams to ensure data governance policies are followed, with a focus on security and compliance. 

• Enterprise Bus Architecture: 

• Contribute to designing and implementing the firm’s Enterprise Bus Architecture, ensuring smooth data exchange between various internal and external systems. 

• Build and manage processes to propagate real-time changes from SQL tables and other systems to the enterprise bus. 

• Ensure the enterprise bus efficiently handles data flows and event-driven processing across the firm’s data ecosystem. 

• Performance Optimization: 

• Continuously monitor and improve the performance of data integration pipelines to ensure optimal throughput and latency. 

• Identify bottlenecks and inefficiencies in existing processes and propose solutions to improve data flow and processing time. 

• Collaboration and Communi