Data Integration Engineer

BLR | Leadership Platforms | CCMI•Dallas, TX

1d•Onsite

About The Position

The Data Integration Engineer is responsible for procuring, integrating, and maintaining external data sources that enhance our platform capabilities. This role focuses on researching and evaluating new data acquisition opportunities, building sustainable data pipelines, and ensuring data quality and accessibility. The Data Integration Engineer will work independently to identify data gaps, research potential solutions including third-party datasets and AI-powered tools, and present recommendations to leadership for strategic decision-making.

Requirements

Demonstrated expertise in data procurement, acquisition, and integration methodologies.
Strong research skills with ability to independently evaluate and compare data providers and technologies.
Proven ability to work independently and drive multiple data initiatives simultaneously.
Excellent analytical and problem-solving skills with keen attention to detail.
Strong communication skills to effectively present technical findings and recommendations to both technical and non-technical stakeholders.
Ability to translate business requirements into data acquisition strategies.
Self-motivated with strong organizational skills and ability to manage competing priorities.
Experience documenting technical processes and creating clear, maintainable data workflows.
Comfortable evaluating emerging technologies including AI-powered data tools.
Ability to work in our Dallas, TX office full-time
Bachelor's degree in Computer Science, Data Science, Information Systems, or related quantitative field
3-5 years of experience in a data analyst, data management or business intelligence role
3-5 years of hands-on experience with a combination of the following technologies:
Programming Languages: SQL, Python (required)
Data Technologies: ETL processes, data pipeline development, REST APIs, web scraping, MySQL/PostgreSQL
Data Tools: Excel, data visualization tools (Tableau, Power BI - preferred), data integration platforms (Talend, Apache Airflow - preferred)
Additional Skills: Data quality and governance principles, AI-powered data tools, cloud platforms (AWS, Azure, Google Cloud - preferred)
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
All external applicants must be legally eligible to immediately work in the country of hire without current or future sponsorship.
If you require an accommodation under the Americans with Disabilities Act, Section 503 of the Rehabilitation Act or similar law in order to apply for employment at Simplify Compliance, please contact our Talent Acquisition Team 1.800.727.5257, ext. 8101.
Job applicants may request to review the company's Affirmative Action plans by contacting the talent acquisition team/recruiter, Human Resources department or Chief People Officer.

Nice To Haves

Experience with data procurement or vendor evaluation processes
Knowledge of data center industry and related data sources
Agile/Scrum methodology experience
Understanding of data privacy regulations (GDPR, CCPA)

Responsibilities

Research and identify external data sources that align with business needs and platform enhancement goals.
Evaluate third-party data providers, subscription services, and alternative data procurement methods including AI tools and web scraping technologies.
Conduct comprehensive cost-benefit analyses of data acquisition options, documenting benefits, limitations, and integration requirements.
Design and implement automated processes to maintain data currency and quality for newly acquired datasets.
Build and maintain data pipelines to integrate data from multiple external sources into company databases.
Develop and document data procurement workflows, integration processes, and maintenance schedules.
Present findings and recommendations to leadership with clear analysis of costs, benefits, and implementation timelines.
Collaborate with product and engineering teams to ensure seamless integration of new data sources into existing systems.
Monitor data quality, identify anomalies, and implement validation checks to ensure accuracy and reliability.
Additional Responsibilities as assigned