We are on a mission to evolve how we use data at Envestnet to grow our business and fulfill the needs of our customers in order to advance our goals of trusted data interoperability. The role of the Data Quality Specialist is to ensure the quality of the data in the Data Lake. They also monitor performance and quality control plans to identify any issues or ways to improve data pipeline processes and designs. This role requires collaborating with data pipeline engineers to implement effective automation processes by developing test cases and frameworks.
You will partner with technical and business stakeholders to implement solutions balancing current and legacy technical standards, while keeping an eye towards scalability and resilience. You will have the opportunity to grow the capabilities of the org to leverage trusted data to deliver against revenue, efficiency, and assurance objectives. We are looking for someone who can be a self-starter and own the accountability of digging into complex legacy processes, bringing together multiple stakeholders and diverse viewpoints, documenting what “good” looks like and reporting on multiple activities in a consolidated, compelling view that tells the story of where we are and where we need to be.
Data Quality Lead Responsibilities
- Validation Development & Implementation
- Data Quality Tools Administration
- Audit Compliance Support/ Participate in monitoring compliance to policies & procedures.
- Data Analysis & Interpretation to identify quality trends in source and processed data
- Prioritize Business Needs - work with management to prioritize business and information needs and identify new processes that will improve the systems in place and define new opportunities.
- Keep management informed on day-to-day activities and potential risks found
- Keep customer engaged by providing feedback on data quality trends and making sure that they are part of the resolution process
- Document and maintain data flow process diagrams, mapping specifications, dictionaries, and lineage.
- Build and maintain the enterprise data quality dashboard.
- Consult with Project Teams to ensure good data quality practices are baked into the lifecycle.
- Assist process, product and platform owners in responding to high priority data issues as they are identified.
- Document, Analyze and Solve data quality issues as prioritized by stakeholders.
- Education: Bachelor Degree in Computer Science or relevant field, Master’s Degree is a plus
- 2 to 5 years of relevant experience.
- Proficiency in programming languages including Structured Query Language (SQL), Python (or other scripted language), and ETL frameworks
- Critical Thinking
- Facilitation of multiple parties
- Getting in to the weeds to make sure things are accurate
- Develop and implement requirements
- Knowledge of data quality, data management, and master data management concepts
- High level of accuracy and attention to detail
- Ability to deal with ambiguous situations
- Understanding of Data Warehousing concepts
- Ability to interface with the business leaders
- Proactive and able to work in an autonomous work environment
- Proven data gathering and analytical skills
- Balancing technical and business focused stakeholder demands while prioritizing action and outcomes.
- Strong networking skills and ability to work across multiple organizations to accomplish diverse goals
- Good understanding of technical data forensics, able to independently research data structures (relational SQL, semi-structured, Excel, Csv, etc.