Data Research Specialist Tableau

At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most.

We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.

The Data Integrity Team is a brand new team with the purpose of ensuring all primary, publicly accessible data collected by our researchers is correct and accurate, allowing the insights produced from this data to be reliable. The Data Integrity team collaborates with other teams while also operating independently. Their responsibilities include monitoring data researched to ensure that errors are identified and caught as soon as possible, creating detective skills for looking for issues and mending them, setting up new configurations and ensuring they are correct, testing new developments to guarantee data quality is not compromised, visualizing data, automating processes, working with relevant technologies, and ensuring data governance and compliance. They play a crucial role in enabling data-driven decision-making and meeting the organization's data needs. 

A typical day in the life of a Tableau Data Integrity Specialist will involve guiding team members through tableau challenges whilst creating new reports and looking for the next set of possible quality assurance problems. They should understand how to automate systems, optimization techniques, and best practices in debugging, testing and looking for issues. They work closely with other team members, offering technical mentorship, as well as advanced Tableau, SQL and Python.
 

• Technical Mentorship and Tableau Report Quality: Mentor team members on standards, optimization, and debugging, while conducting report reviews to enforce high consistent quality. Provide constructive feedback, and enforce quality standards.
• Technical Mentorship and Code Quality: Mentor team members on coding standards, optimization, and debugging while conducting code reviews to enforce high code quality. Provide constructive feedback, and enforce quality standards.
• Testing and Quality Assurance Leadership: Lead the development and implementation of rigorous testing protocols to ensure project reliability and advocate for automated test coverage.
• Process Improvement and Documentation: Establish and refine standards for version control, documentation, automation and task tracking to improve productivity and data quality. Continuously refine these processes to enhance team productivity, streamline workflows, and ensure data quality.
• Hands-On Technical Support: Provide expert troubleshooting support in Tableau, Python, MySQL helping the team resolve complex technical issues. Provide on-demand support to team members, helping them overcome technical challenges and improve their problem-solving skills.
• High-Level Technical Mentorship: Provide mentorship in advanced technical areas, including best practices, data visualization and programming. Guide the team in building scalable and reliable solutions to continually track and monitor data quality.
• Cross-Functional Collaboration: Partner with other teams to align tableau visualizations, data requirements, testing protocols, and process improvements. Foster open communication across teams to ensure seamless integration and delivery of data solutions.
• Continuous Learning and Improvement: Stay updated with emerging best practices, sharing relevant insights with the team. Drive a culture of continuous improvement, ensuring the team’s skills and processes evolve with industry standards.
• Data Pipelines: Design, implement and maintain scalable data pipelines for efficient data transfer, transformation, and visualization in production environments.
   

• Educational Background: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. Equivalent experience in data engineering roles will also be considered.
• Leadership and Mentorship: Demonstrated ability to mentor and support junior and mid-level engineers, with a focus on fostering technical growth and improving team cohesion. Experience leading code reviews and guiding team members in problem-solving and troubleshooting.
• Technical Proficiency:
• Tableau: Advanced knowledge of Tableau and Tableau Prep Builder, with experience in creating efficient reports, data pipelines and workflows. Knowledge of Tableau Server Administration would be advantageous.
• Programming: Expert-level skills in MySQL and Python, with a strong understanding of code optimization, debugging, and testing. The ability to understand modular, reusable, and efficient code structures. Experience in implementing OOP best practices to enhance code organization and maintainability.
• Data Integrity & Validation Experience: Strong ability to assess, validate, and ensure the integrity of large datasets with experience in identifying data inconsistencies, anomalies, and patterns that indicate data quality issues. Proficient in designing and implementing data validation frameworks.
• Analytical & Problem-Solving Mindset: Critical thinking with a habit of asking "why"—why anomalies exist, why trends deviate, and what underlying factors are at play. Strong diagnostic skills to identify root causes of data issues and propose actionable solutions. Ability to work with ambiguous data and derive meaningful insights along with handling complex technical issues. Serve as a key resource for team troubleshooting, guiding others through debugging and technical problem-solving.
• Attention to Detail: Meticulous attention to data nuances, capable of spotting subtle discrepancies. Strong focus on data accuracy, completeness, and consistency across systems.
• Testing and QA Expertise: Proven experience in designing and implementing testing protocols, including unit, integration, and performance testing. 
• Process-Driven Mindset: Strong experience with process improvement and documentation, particularly for coding standards, task tracking, and data management protocols.
• Strong Communication Skills: Ability to clearly articulate technical challenges, propose effective solutions, and align cross-functional teams on project requirements and data workflows. Strong at conveying complex ideas to both technical and non-technical stakeholders, ensuring transparency and collaboration. Skilled in documenting data issues, methodologies, and technical workflows for knowledge sharing.
• Adaptability and Continuous Learning: Stay updated on data engineering trends and foster a culture of continuous learning and process evolution within the team.
• Data Pipelines: Hands-on experience in building, maintaining, and optimizing ETL/ELT pipelines, including data transfer, transformation, and visualization, for real-world applications. Strong understanding of data workflows and ability to troubleshoot pipeline issues quickly with the ability to automate repetitive data processes to improve efficiency and reliability.
   

• Day off on the 3rd Friday of every month (one long weekend each month)
• Monthly Wellness Reimbursement Program to promote health well-being
• Monthly Office Commutation Reimbursement Program
• Paid paternity and maternity leaves