Data Integrity Manager
Data Integrity Manager
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Job Description
Responsibilities:
Technical Mentorship and Code Quality: Mentor team members on coding standards optimization and debugging while conducting code and report 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 and task tracking to improve productivity and data quality. Continuously refine these processes to enhance team productivity streamline workflows and ensure data quality.
HandsOn Technical Support: Provide expert troubleshooting support in Python MySQL GitKraken Tableau and Knime helping the team resolve complex technical issues. Provide ondemand support to team members helping them overcome technical challenges and improve their problemsolving skills.
HighLevel Technical Mentorship: Provide mentorship in advanced technical areas including best practices data visualization and advanced Python programming. Guide the team in building scalable and reliable solutions to continual track and monitor data quality.
CrossFunctional Collaboration: Partner with data scientists product managers and data engineers to align 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 data engineering methodologies and best practices sharing relevant insights with the team. Drive a culture of continuous improvement ensuring the teams 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.
Qualifications :
Skills and Experience:
Educational Background: Bachelors or Masters degree in Computer Science Data Engineering or a related field. Equivalent experience in data engineering roles will also be considered.
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 & ProblemSolving Mindset: Critical thinking with a habit of asking whywhy 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.
Attention to Detail: Meticulous attention to data nuances capable of spotting subtle discrepancies. Strong focus on data accuracy completeness and consistency across systems.
Technical Proficiency:
Programming: Expertlevel skills in Python with a strong understanding of code optimization debugging and testing.
ObjectOriented Programming (OOP) Expertise: Strong knowledge of OOP principles in Python with the ability to understand modular reusable and efficient code structures. Experience in implementing OOP best practices to enhance code organization and maintainability.
Data Management: Proficient in MySQL and database design with experience in creating efficient data pipelines and workflows.
Tools: Advanced knowledge of Tableau. Familiarity with Knime or similar data processing tools is a plus.
Testing and QA Expertise: Proven experience in designing and implementing testing protocols including unit integration and performance testing.
ProcessDriven Mindset: Strong experience with process improvement and documentation particularly for coding standards task tracking and data management protocols.
Leadership and Mentorship: Demonstrated ability to mentor and support junior and midlevel engineers with a focus on fostering technical growth and improving team cohesion. Experience leading code reviews and guiding team members in problemsolving and troubleshooting.
ProblemSolving Skills: Ability to handle complex technical issues and serve as a key resource for team troubleshooting. Expertise in guiding others through debugging and technical problemsolving.
Strong Communication Skills: Ability to clearly articulate technical challenges propose effective solutions and align crossfunctional teams on project requirements technical standards and data workflows. Strong at conveying complex ideas to both technical and nontechnical 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: Handson experience in building maintaining and optimizing ETL/ELT pipelines including data transfer transformation and visualization for realworld 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.
Additional Information :
Perks:
Day off on the 3rd Friday of every month (one long weekend each month)
Monthly Wellness Reimbursement Program to promote health wellbeing
Monthly Office Commutation Reimbursement Program
Paid paternity and maternity leaves
Remote Work :
Yes
Employment Type :
Fulltime
Employment Type
Remote
