About GDH
Sourced by ZipRecruiter
Industry
It services
Company size
201 - 500 Employees
Headquarters location
Tulsa, OK, US
Year founded
2001
$75 - $82.27/hr
Other
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Job description
Role Summary
A data driven financial services organization seeks a Data Product Analyst to join their Enterprise Data Products Team. This role is focused on supporting the replacement of the Fraud Case Management system, emphasizing data analysis, sourcing, and quality assurance. The analyst will collaborate closely with IT and Data Engineering teams to ensure data is well-defined, high-quality, and ready for deployment within AWS, leveraging a strong data product mindset.
Responsibilities
- Perform advanced SQL analysis across large, complex datasets to support data project needs.
- Document data sourcing, lineage, and transformation processes from source systems to target environments.
- Develop and maintain source-to-target mappings, data dictionaries, and metadata repositories.
- Define data structure and quality expectations for data landing in AWS environments.
- Identify, document, and address data quality issues while monitoring data quality rules.
- Prepare clear and precise requirements and artifacts to assist Data Engineers in building data pipelines.
- Make data-driven recommendations to optimize data usability and quality.
- Collaborate effectively with cross-functional teams within an Agile/Scrum framework.
- Ensure data processes align with organizational standards and best practices.
- Maintain knowledge of evolving data tools, cloud services, and industry trends to support ongoing improvements.
Qualifications
- Strong expertise in SQL, with experience analyzing large and disparate datasets.
- Proven experience supporting large-scale data projects in cloud environments, particularly AWS.
- Hands on experience working with cloud services such as AWS Glue and Lambda.
- Familiarity with Snowflake or similar cloud data platforms; AWS preferred.
- Experience working within Agile/Scrum teams and frameworks.
- Excellent communication and documentation skills, with a collaborative mindset.
- Ability to partner effectively with IT and Data Engineering teams.
- Availability to work in a hybrid schedule, combining remote and in-office work.
- Work rights to support employment in the designated location.
Publishing Pay Range: $75.00 - $82.27 Hourly
This position offers a hybrid schedule, with time split between the office and remote work.
gdhinc.com
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Analyst?
A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.
Q: What is the career path for a Data Analyst?
A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.