This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Manager, Data Engineering - REMOTE. In this pivotal role, you will be responsible for overseeing a talented team of data engineers, guiding them through the intricacies of developing and managing data systems. You will engage closely with your team to streamline operational processes, enhance data quality, and ensure the reliability of our data pipelines. Your expertise will not only shape technical strategies but also foster a collaborative culture that empowers engineers to excel. Ultimately, your contributions will drive innovations that support client needs and advance organizational goals. - Lead a group of engineers focused on rapidly developing, scaling, and supporting data products for consumption by clients and business stakeholders - Be actively engaged in problem-solving and solution design - Own data engineering delivery outcomes (timelines, tradeoffs) - Simplify existing pipelines and architectures where complexity or fragmentation has crept in - Define and incorporate best practices to uphold quality, reliability, and operational sanity - Partner with business and engineering stakeholders to understand needs, align priorities, and translate them into shipped solutions - Foster a proactive, can-do, and execution-oriented culture Qualifications - 5+ years of experience building and running data systems in production - 1+ years of experience managing technical projects as an engineering lead and/or people manager - Comfort working across SQL and Python in modern distributed data platforms - Aptitude for designing and understanding data systems with varied layers of interdependency - Working knowledge of data security and governance standards - Exposure to data visualization tools such as Databricks AI/BI, PowerBI, Tableau, etc. Benefits - Competitive salary range: $124,100 - $179,700 - Bonus/Variable Pay: 15% - Flexible working hours - Opportunities for growth and professional development - Collaborative and inclusive team culture - Health and wellness benefits - Remote work opportunity

• Define partner onboarding and clean room architecture patterns across Snowflake, LiveRamp, and Databricks that are secure, scalable, and repeatable. • Configure and manage partner-specific clean room environments; deploy and manage Python-based libraries within the platform ecosystem. • Establish and maintain MLOps practices, including model serving, monitoring, and pipeline orchestration for AI/ML features deployed within the platform ecosystem. • Own design and enforcement of granular RBAC policies and least-privilege service accounts. • Serve as the technical lead for onboarding new partners, implementing privacy-preserving controls (e.g., aggregation thresholds and anonymization techniques). • Design, build, and operate scalable ELT pipelines using Snowpark and/or PySpark and advanced SQL to provision Gold datasets. • Implement and evolve identity resolution logic mapping internal data to 3P identifiers (including LUIDs, RampIDs, TransUnion IDs), ensuring privacy-safe practices. • Design and operate scalable data architectures across Snowflake and Databricks supporting batch and near real-time processing patterns. • Build robust automated checks (e.g., Great Expectations or custom SQL assertions) and define quality standards to detect schema drift, null rate spikes, and volume anomalies. • Lead performance optimization across platforms (query tuning, caching, incremental processing) and define and implement query tagging and chargeback models for accurate cost attribution. • Establish monitoring, alerting, runbooks, and standard operating procedures to improve platform reliability and reduce incident time-to-resolution. • Validate that output data adheres to privacy and business requirements, and define test strategies for partner-facing releases. • Serve as the escalation point for diagnosing connection failures, data discrepancies, or latency issues with partner technical teams. • Design and build internal AI agents (using frameworks like LangChain, Snowflake Cortex) and mentor other engineers through code reviews, design discussions, and operational best practices.

• Plan and align the project with the Androidization strategy • Gather and validate functional and technical requirements • Design the solution architecture and data model • Automate the integration and processing of operational data • Model and automate refined tables with business rules • Implement proactive monitoring and alerts • Publish and validate tables in the production environment • Document the entire technical and functional structure of the platform • Conduct training sessions and formalize the technical handover

• Plan and align the project with the Androidization strategy • Collect and validate functional and technical requirements • Design the solution architecture and data model • Automate the integration and processing of operational data • Model and automate refined tables with business rules • Implement proactive monitoring and alerts • Publish and validate the tables in the production environment • Document the entire technical and functional structure of the platform • Conduct trainings and formalize the technical handover