Data Quality Engineer

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Pay found in job post

Retrieved from the description.

Base pay range

$110,000.00 / yr - $135,000.00 / yr

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We have partnered with our client in their search for a Data Quality Engineer.

The individual in this role will have the opportunity to oversee the development and execution of data validation strategies across the organization to ensure data integrity, accuracy, and alignment with company standards. This individual will guide team members in applying best practices for test design and planning and estimating high-impact data workflow modifications, while identifying opportunities for automating data quality checks.

Responsibilities

• Collects, analyzes, and validates data before it is stored for organizational use, ensuring accuracy across changes to views, stored procedures, batch processes, and diverse data sources.
• Collaborates with product and data teams to test and deploy data workflow modifications based on collaboratively defined data transformation and integration requirements.
• Participates in work refinement and estimation processes with data and product teams.
• Prepares and executes testing on all new and modified code, ensuring compliance with organizational data quality standards.
• Works with data, product, and change control teams to ensure quality data deliverables that provide customer value.
• Creates and maintains documentation related to data flows, integration processes, support processes, and system changes, as defined by team and company standards.
• Ensures timely delivery of data testing tasks and projects and communicates delays or roadblocks with team leadership as needed.
• Collaborates with product and data teams to design, develop, test, and deploy high-impact data workflow modifications, including ETL / ELT processes that align with business data requirements.
• Reviews test creation, planning, and execution results for all stages of testing, with a focus on validation where necessary.
• Provides coaching, mentorship, and guidance for testing automation within the DevOps lifecycle, ensuring team deliverables are met.
• Develops and implements data testing methodologies, standards, and best practices, including those related to data processes.
• Applies standard statistical analysis and / or financial models to verify data acceptability and accuracy.
• Identifies opportunities for process improvement, specifically in data collection processes, and collaborates with the team to correct deficiencies in systems.
• Identifies and resolves data anomalies, ensuring that missing data is gathered and entered to maintain data accuracy.
• Provides insights for defect-prone areas in the architecture based on metrics, root cause analysis, and organizational impacts.
• Leads the resolution process for defects in data workflows, including processes, designing and implementing metrics, dashboards, and reporting capabilities.
• Troubleshoots, resolves, and communicates production issues related to data processing and data workflows.
• Guides the automation of data validation processes and finds opportunities to extend automation beyond current workflows.
• Mentors and shares knowledge with junior team members to enhance skills in testing, automation, and data validation.
• Identifies and implements improvements in process efficiencies, with a focus on data quality and user experience.
• Guides the evolution of team-level best practices for data processes and quality assurance while considering their broader organizational impact.
• Leads efforts to identify, review, refine, and resolve complex efficiency / effectiveness related issues, mobilizing the team to find solutions and improve processes with an emphasis on quality and positive user experience.
• Utilizes specialized knowledge, experience, and creativity to develop multiple potential solutions, drawing on input from team members.
• Guides the team in evaluating and communicating the pros and cons of all potential solutions, considering impacts on data quality and business processes.
• Implements quality assurance practices to ensure data integrity throughout data workflow processes and proactively resolves any anomalies.
• Understands and effectively communicates the relationships and dependencies between application components.
• Collaboratively guides evolution of team-level development best practices, standards, and policies, taking into consideration team, product, architecture, and business priorities.
• Consistently acts according to our customer experience standards, including responding quickly, maintaining a positive attitude, building rapport, demonstrating empathy, managing the customer's expectations, using the proper communication channel for the situation, and taking ownership to ensure the customer's issue is resolved.
• Collaborates with direct teammates, product team leadership, managers, vendors, and business partners to ensure quality data integration processes.
• Flexes to non-core responsibilities, including analysis, testing, deployment, and facilitation to ensure timely work delivery to stakeholders.

Skills Required

Data Quality Engineer

Edina, MN (Hybrid, onsite 1-2x every 2 weeks)

Insruance

Conversion salary $110,000-135,000 / year

Ref ID

About Korn Ferry

Korn Ferry unleashes potential in people, teams, and organizations. We work with our clients to design optimal organization structures, roles, and responsibilities. We help them hire the right people and advise them on how to reward and motivate their workforce while developing professionals as they navigate and advance their careers. To learn more, please visit Korn Ferry at ; / span>

Seniority level

Seniority level

Mid-Senior level

Employment type

Employment type

Full-time

Job function

Job function

Quality Assurance

Industries

Software Development

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