At NetWitness, we believe in challenging the established mindsets, approaches, and product categories in the information security industry. Every product that we deliver to market is based on a core set of principles grounded in the major paradigm shifts in play and the implications that they have for our customers. Do the right thing – by our customers, employees, and shareholders...think long-term, but act with a sense of urgency. What we do matters – our work makes a difference in the world. We give a damn – about our customers, about what we’re doing, about each other...we’re in this together. We are a fun company – building cool products with technical insight that help our customers solve meaningful problems. Our mission is delighting our customers with everything we do. We provide thousands of customers around the world with essential security capabilities, leading with our Intelligence Driven Security Strategy and Vision, to protect their most valuable assets from cyber threats. With NetWitness’s award-winning products, organizations effectively detect, investigate, and respond to advanced attacks; reduce IP theft and cybercrime.
Data Product Manager
Location
Worldwide
Posted
17 days ago
Salary
0
Seniority
Lead
No structured requirement data.
Job Description
Data Product Manager
Partner One Capital
Role Description SafeGraph is a Data as a Service (DaaS) company focused on curating the most accurate, precise, and fresh points of interest (POI) database. You will play a critical role in shaping how our data products are built, validated, and trusted. This role combines product thinking with hands-on technical execution. - Drive AI-powered product initiatives while owning the data quality processes. - Collaborate with the Product team and work closely with Customer Success, Sales, and Engineering. - Identify data integrity risks early, accelerate investigations, and ship better data. Qualifications - 2-4 years in a technical product management or analytics role at a data-heavy company. - Strong technical expertise in working with dataframes and complex data manipulation (Python, SQL, Pandas, Spark). - Experience in building and implementing QA for datasets. - A bias for automating repetitive tasks and reproducibility. - Experience using AI tooling to accelerate data analysis, investigation, and documentation. - Professional-level English proficiency, as English is the primary working language across the company. Requirements - Manage initiatives to improve data product offering. - Investigate data quality issues independently and own the full feedback loop. - Design, develop, and implement QA procedures to proactively identify and prevent data integrity issues. - Build repeatable, automated checks to reduce reliance on manual investigation. Nice to Have - Experience owning or contributing to AI/ML-adjacent product initiatives. - Experience with large geospatial datasets. - Experience with Pyspark, Scala, and Apache Sedona. - Experience communicating directly with customers. What Success Looks Like - Robust QA processes running in production. - AI product initiatives shipping without needing close management. - Data quality issues resolve faster, with fewer escalations to engineering and clear communication to CS and customers.
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