Mid Data Ops Analyst

4-6 years of hands-on experience in data-focused roles Proficient in performing advanced SQL queries for research and reporting Track record of analyzing large datasets, mining for inconsistencies and recognizing patterns Capable of rectifying data inconsistencies and developing scalable data quality test plans Proficient in managing product lifecycles and communicating action plans and timelines to clients Experience collaborating with Engineering and Data Science teams Ability to think strategically and translate client requirements into actionable strategies Collaborate strategically with product and commercial teams Strong communication skills with experience in managing stakeholders Proficient decision-making skills, adept at prioritizing tasks and project managing cross-functional teams Efficient management of data processes and documentation Expert in SQL, Excel, DBT and business intelligence tools (e.g. Looker, Redash) Comfortable navigating complex ETL systems and messy data Proven ability to organize, analyze and vet large volumes of data with great attention to detail Self-starter with the ability to carry multiple initiatives, prioritize time and resources, and meet deadlines

Investigate anomalous data to determine data quality errors or real-world events. Act as the first responder for data issues and inquiries. Educate commercial stakeholders about data definitions and nuances. Manage updates to QA tests and dashboards. Investigate data restatements and data science models. Coordinate data fixes with internal and external teams. Perform data quality investigations to understand discrepancies with customer data. Present findings to customers directly. Run new coverage feasibility studies and propose solutions. Coordinate monthly data releases in Looker. Coordinate weekly data releases via ad hoc reports.