Data Architect – Data Modeling

Job Description

Job Title: Data Architect – Data Modeling
Job Location: Atlanta, GA (Onsite) United States
Job Duration: 6+ Months

Type of Hire: Contract
Mode of Interview: Video Interview.
No. of Opening: 1

JOB DETAILS:

Position Overview: Data Architect – Data Modeling

Location: Atlanta, GA (Onsite)
6+ Months Contract

Rate-$70/hr. on C2C
We are seeking a highly skilled and motivated Data Architect to join our Business Intelligence (BI) team. As a Data Architect, you will play a crucial role in designing, implementing, and maintaining the data infrastructure necessary to support our BI initiatives. Your expertise in data modeling and Extract, Transform, Load (ETL) processes will be instrumental in transforming raw data into valuable insights, empowering our organization to make informed, data-driven decisions. This is an exciting opportunity to work with cutting-edge technologies and collaborate with a dynamic team to drive the growth and success of our company.

Responsibilities:

1. Data Modeling: Design, develop, and maintain robust and scalable data models that support the organization’s BI and analytical requirements. This includes conceptual, logical, and physical data modeling to ensure data consistency, accuracy, and efficiency.

2. Data Mapping and Documentation: Document data architecture, data flows, and ETL processes for reference and future enhancements. Research and consolidate data sources and detailed logic in order to build harmonized data models.

3. ETL Development: Build and optimize ETL processes to efficiently extract data from various sources, transform it into a usable format, and load it into the data warehouse or BI platform. Implement data integration and cleansing strategies to ensure data quality.

4. Data Warehouse Design: Collaborate with the BI team to design and implement data warehousing solutions that facilitate easy access to data for reporting and analysis purposes. Ensure the data architecture aligns with business needs and objectives.

5. Performance Optimization: Continuously evaluate and improve the performance of data models and ETL processes to enhance data processing speed and query efficiency. Identify and resolve bottlenecks or performance issues.

6. Data Governance and Security: Establish and enforce data governance practices to maintain data integrity, security, and compliance with industry standards and regulations. Implement data access controls and encryption techniques to safeguard sensitive information.

7. Collaboration and Documentation: Work closely with cross-functional teams, including data analysts, data engineers, and BI developers, to understand data requirements and provide technical solutions. Document data architecture, data flows, and ETL processes for reference and future enhancements.

8. Data Quality Assurance: Develop and execute data validation procedures to ensure the accuracy and reliability of data stored in the data warehouse or BI system. Implement data profiling and monitoring mechanisms to proactively detect anomalies.

9. Stay Current with Technology Trends: Keep abreast of the latest developments in data architecture, data modeling, ETL tools, and BI technologies. Propose and implement innovative solutions to enhance the BI team’s capabilities.

Qualifications:

– Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.

– Proven experience as a Data Architect, Data Modeler, or similar role with a focus on supporting Business Intelligence teams.

– In-depth knowledge of data modeling techniques, such as entity-relationship diagrams, dimensional modeling, and data normalization.

– Proficiency in designing and implementing ETL processes using tools like Informatica, Talend, or similar.

– Strong understanding of data warehousing concepts and best practices.

– Familiarity with BI tools such as Tableau, Power BI, or QlikView, and ability to work with BI developers and analysts to deliver meaningful insights.

– Solid understanding of database technologies (e.g., SQL, NoSQL), data integration techniques, and data governance principles.

– Excellent analytical and problem-solving skills with the ability to translate business requirements into technical solutions.

– Strong communication and collaboration skills to work effectively with cross-functional teams.

– Detail-oriented with a passion for data quality and accuracy.

– Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud) is a plus.