• Participate in cross-functional meetings to define project objectives and scope. • Analyze and prioritize business requirements related to data. • Design and develop data extraction, transformation, and loading pipelines (ETL/ELT). • Develop applications for extracting data from various sources and formats (JSON, XML, PDF, etc.). • Write clean, efficient, and scalable code, adapting to new technologies as needed. • Implement data quality methodologies throughout ingestion and transformation processes. • Optimize services, queries, and processes to reduce operational costs and improve performance. • Validate the functionality, integrity, and security of data engineering processes.

• Design, develop, and maintain scalable and efficient data pipelines (ETL/ELT). • Build and optimize modern data architectures (Data Warehouse and Lakehouse). • Implement data models (primarily dimensional modeling using the Kimball approach). • Integrate multiple data sources ensuring quality, consistency, and availability. • Perform data profiling and anomaly detection. • Optimize SQL queries and performance across data platforms. • Collaborate on defining standards, best practices, and data architecture. • Implement CI/CD processes and DevOps practices applied to data pipelines. • Work under Agile methodologies (Scrum/Kanban) in collaboration with multidisciplinary teams.

• Serve as a technical expert for Snowflake and Azure , leading hands ‑ on implementation across ingestion, transformation, orchestration, and platform optimization. • Develop and maintain API ‑ driven integrations using MuleSoft , enabling secure, scalable connectivity between cloud and on ‑ prem systems. • Drive the migration from on ‑ prem SQL Server environments to Snowflake , including re ‑ architecting pipelines, data models, and workflows for the cloud. • Implement engineering best practices, including CI/CD for data, infrastructure ‑ as ‑ code, version control, testing frameworks, and observability. • Independently troubleshoot complex data and platform issues , identifying root causes and designing effective long ‑ term solutions. • Collaborate with data architects, analysts, and business partners to translate requirements into robust, production ‑ ready solutions. • Mentor and support data engineers , providing technical guidance, code reviews, and thought leadership to elevate engineering standards. • Optimize data models, storage patterns, and compute usage to ensure cost ‑ efficient and high ‑ performance operations. • Partner with IT, security, and governance teams to ensure compliance, data quality, and secure handling of sensitive healthcare data. • Evaluate and introduce new tools, frameworks, and cloud capabilities that enhance our data platform and engineering productivity.

Job Title Data EngineerJob Description Summary Job Description The Salesforce Data Engineer plays a critical role in enabling seamless data integration, reporting, analytics, and governance across Cushman & Wakefield's Salesforce ecosystem. This individual will focus on designing and executing scalable data solutions to ensure high-quality, reliable data that drives business insights and collaboration. As a technical expert, the Data Engineer will work across teams to address complex data challenges, automate workflows, and support integration with external systems. Also helps in developing Automation scripts and workflows to streamline data processing tasks within Salesforce. Job Description Responsibilities: - Data Strategy Execution: Implement and optimize data integration pipelines to support business development, analytics, and collaboration needs. - Data Quality Management: Monitor and maintain data accuracy, identify, and resolve issues, and enforce governance standards to uphold Salesforce data integrity. - Integration and Migration: Develop and manage workflows for migrating data from various sources, including CRM systems, databases, and spreadsheets, into Salesforce using tools such as Data Loader and APIs. - Third-party Integration: Contribute thought leadership to the development and evolution of Digital Enablement methodologies and build the framework and infrastructure to provide connectivity (APIs) to core business applications (Salesforce) using ZoomInfo, Ring Lead and D&B applications. - Analytics and Reporting: Collaborate with stakeholders to design and implement dashboards, metrics, and reporting solutions for actionable insights. - Automation: Build scripts and solutions to automate data cleansing, transformation, and integration processes. - Support and Troubleshooting: Address data-related tickets and escalations, providing timely solutions to meet business requirements. - Optimization: Identify opportunities for improving data management practices, including integration patterns, performance tuning, and scalability. - Collaboration: Partner with project managers and cross-functional teams to deliver data-driven solutions aligned with business objectives. Qualifications: - 2-3 years of experience in data engineering, integration, or analytics roles, preferably in Salesforce ecosystems. (5+ preferred) - Strong understanding of Salesforce data structures, API integration, and CRM workflows. - Experience designing systems which incorporate data from various systems to make Company data and user contact profiles a plus. - Bachelor’s Degree in Computer Science, Engineering, IT or other related fields - Hands-on experience with ETL tools, Salesforce Data Loader, Workbench, or similar platforms. - Proficient in SQL and data modeling techniques to write complex, highly optimized queries across large volumes of data. - Demonstrated ability to work with large datasets, ensuring quality and consistency. - Proficiency in data visualization tools like Tableau, CRM Analytics, Salesforce Reports or Salesforce Dashboards. - Strong problem-solving and critical-thinking skills. - Excellent written and verbal communication abilities. Preferred Skills: - Experience with external data integration platforms (e.g., MuleSoft, Informatica, or Dell Boomi). - Familiarity with programming languages (e.g., SQL, SOQL, JavaScript) for data manipulation and automation. - Knowledge of cloud-based data storage and processing platforms like AWS, Azure, or Google Cloud. Business Experience: - Proven success in working within customer-centric organizations, delivering scalable and customer-focused solutions. - Adept at juggling multiple assignments and meeting aggressive timelines within dynamic environments. Skills & Personal Qualities: - Collaborative mindset with a proactive approach to identifying and resolving challenges. - Strong service orientation and commitment to enabling data-driven decision-making. - Comfort with working in a fast-paced and evolving business landscape. INCO: “Cushman & Wakefield”