DATA INTEGRATION ENGINEER RESUME EXAMPLE

Published: September 27, 2024 - The Data Integration Engineer collaborates with various company stakeholders to define and document data needs, ensuring the design, consumption, and protection of data meet established standards. This role involves designing and implementing efficient data pipelines between applications and a data lake, facilitating trustworthy data models that support self-service analytics and reporting. Additionally, the engineer develops and governs data architectures, contributes to data strategy, and supports the integration infrastructure within the Swatch Group Services Integration Competence Center.

Tips for Data Integration Engineer Skills and Responsibilities on a Resume

1. Data Integration Engineer, Tech Innovations LLC, Austin, TX

Job Summary:

  • Design and Develop solutions utilizing Integration Best Practices;
  • Provide day-to-day support and technical expertise to other engineers, project owners and stakeholders;
  • Provide strategy, architecture, design and automation options to increase efficiency and simplify integration across multiple platforms
  • Provide IT leadership by representing the integration team to IT and the business as well as mentoring other team members.
  • Configure and maintain data integration solutions to connect and synchronize internal Uber systems with our sales compensation system
  • Build a secure, near-real-time single source of truth/database for all sales compensation-related data
  • Be the go-to data expert for our business stakeholders
  • Adhere to and improve upon rigorous documentation and DevOps processes
  • Collaborate and coordinate with internal and external business partners in developing or enhancing systems, processes, and procedures
  • Support the management, development, ongoing maintenance, and technical support of Sales Compensation data integration platform and other ancillary applications that integrate to support all sales compensation business functions


Skills on Resume: 

  • Integration Solution Design (Hard Skills)
  • Technical Support and Expertise (Hard Skills)
  • Automation and Efficiency (Hard Skills)
  • Leadership and Mentorship (Soft Skills)
  • Data Integration Configuration (Hard Skills)
  • Database Development (Hard Skills)
  • Data Expert (Hard Skills)
  • Documentation (Hard Skills)

2. Data Integration Engineer, Cloud Solutions Corp, Denver, CO

Job Summary:

  • Develop SQL-based integrations and configure interfaces with APIs, HL7, FHIR, and other healthcare standards to transform data sets into our system, powering automated workflows and analytical applications for healthcare providers
  • Establish automated jobs for integrating data from proprietary systems (e.g. Electronic Medical Records and healthcare billing systems) and public data sets (e.g. Medicare)
  • Design and optimize standard interfaces for specific data source systems
  • Build and implement monitoring processes for all data pipelines
  • Work on design and scaling of analytical pipelines on top of data that use both relational database and ElasticSearch technologies.
  • Design, development, and support of data integration solutions. 
  • Partners with internal business units, analysts, vendors, and key stakeholders to understand information requirements to independently design, develop and implement data integration solutions that support our platform resiliency, stability, and supportability; using a variety of ETL, API and database technologies. 
  • Support business decisions, and could span across multiple areas such as consumer experience, clinical quality, hospital operations, supply chain, finance, etc. 
  • Contribute to custom implementation of Data Integration and distribution solutions between different Swatch Group Brands and Countries. SSOT (Single Source of Truth) Solution is a custom-built Data Hub using MS SQL database and Software AG’s Webmethods product stack. 
  • Implement, operate and extend the solution into Data Integration areas


Skills on Resume: 

  • SQL Proficiency (Hard Skills)
  • API Integration (Hard Skills)
  • Data Pipeline Development (Hard Skills)
  • ETL Processes (Hard Skills)
  • Database Management (Hard Skills)
  • Monitoring Processes (Hard Skills)
  • Cross-Functional Collaboration (Soft Skills)
  • Custom Implementation (Hard Skills)

3. Data Integration Engineer, DataStream Analytics, Raleigh, NC

Job Summary:

  • Partner with stakeholders across the company (customer success, community, sales, marketing, finance and product) to establish and document data requirements 
  • Establish processes and governance around data design, consumption and protection
  • Establish operating processes to ensure operational excellence and openness
  • Develop a strong understanding of source data. Use this knowledge to design and build data integrations between applications, with our data lake and from our data lake into trustworthy and readily consumable data models
  • Partner with business domain experts, data analysts and engineering teams to build foundational data sets that are trusted, well understood, aligned with business strategy and enable self-service reporting and analytics 
  • Build reliable, efficient, testable, documented and maintainable data pipelines
  • Identify, document and promote data architecture & data engineering best practices
  • Contribute to knowledge repositories with a particular focus on documenting source system schemas showing keys, relationships, and cardinality
  • Contribute to, and champion, the overall data and BI strategy
  • Design robust data integration architecture and data models
  • Assist in the Governance of master data, interfaces and related processes
  • Support of the Integration Landscape- infrastructure, solutions and applications assigned to Swatch Group Services- Integration Competence Center (INTCC)


Skills on Resume: 

  • Stakeholder Partnership (Soft Skills)
  • Data Governance (Hard Skills)
  • Process Optimization (Hard Skills)
  • Source Data Understanding (Hard Skills)
  • Collaboration with Business Experts (Soft Skills)
  • Data Pipeline Development (Hard Skills)
  • Best Practices Promotion (Hard Skills)
  • Data Integration Architecture Design (Hard Skills)