• Design, build, and maintain robust, scalable data pipelines and ETL/ELT workflows • Develop and manage data warehousing solutions to support business intelligence and analytics needs • Ensure data quality, integrity, and availability across all data systems and sources • Collaborate with data scientists, analysts, and product teams to understand and fulfill data requirements • Optimize query performance and database architecture for speed and efficiency • Monitor, troubleshoot, and resolve data pipeline failures and incidents • Implement and enforce data governance, security, and compliance best practices • Document data models, processes, and infrastructure to support team knowledge sharing

Role Description We are looking to hire a Data Migration Specialist who can facilitate the transfer of data from customers’ prior software to our platform. You’ll collaborate closely with onboarding, support, product, and engineering teams to translate customer data from legacy systems and spreadsheets into structured, clean, and usable datasets. This is a customer-facing role requiring technical skill, attention to detail, and strong communication abilities. Our small and dynamic team (currently 40 people) reports directly to the VP of Customer Success. Duties and Responsibilities - Data Analysis and Mapping - Review customer data (CSVs, spreadsheets, software databases) to assess structure, quality, and completeness - Map legacy data fields to our platform’s schema using internal tools, AI (Chat GPT) or custom scripts - Migration Execution - Transform, clean, and normalize customer data - Import data into Gymdesk customer environments and validate against expected outputs - Perform iterative migrations and troubleshoot errors during the process - Product Expertise and Manual Data Entry - When required, fill any migration gaps with manual data entry - Become an expert in Gymdesk’s product, enabling the ability to set up configurations on behalf of a customer - Customer Communication - Coordinate with onboarding specialists and customers to collect requirements and data formats - Provide status updates, clarify data issues, and assist customers in understanding field-level discrepancies - Collaboration and Process Improvement - Work with product & engineering to report bugs or suggest tooling enhancements - Document migration processes and maintain internal guides for repeatable success Qualifications - 3+ years of experience in data migration, data analysis, business intelligence, or a similar technical role - Proficiency in handling spreadsheets, CSV files, text encoding, date formats, and data cleansing techniques - Experience working with SaaS platforms, CRM, ERP, or customer-facing data workflows - Strong analytical and problem-solving skills with exceptional attention to detail - Excellent written and verbal communication skills - Experience working in customer-facing or onboarding roles is a plus - Knowledge of SQL and at least one scripting language (e.g., Python) is preferred - Understanding of data privacy regulations (e.g., GDPR) is a plus - Experience building or working with internal tools for data migration - Exposure to project management and collaboration tools (e.g., Notion, Jira, Slack) Success Metrics - Percentage of migrations completed within the designated SLA (e.g., 5–7 days for Tier 1 clients) - Accuracy of migrated records and field mappings - Customer satisfaction scores (CSAT, NPS) post-onboarding - Positive internal team feedback on collaboration and adherence to process Benefits - Permanent remote work flexibility - Paid Time Off - Health Maintenance Organization (HMO) coverage - Annual performance bonuses - Dedicated coaches offer an extra channel of support and skill-building - Opportunities for professional growth

• Design and build scalable data quality frameworks and validation systems that process financial data at enterprise scale and across diverse datasets • Own services end-to-end, from architecture and implementation through deployment and operational support • Build tools and interfaces that enable operations teams to efficiently identify, investigate, and resolve data issues • Design and deploy resilient, scalable cloud-native infrastructure on AWS using Terraform • Collaborate with cross-functional teams including product managers, data engineers, and operations stakeholders to deliver high-impact features • Work with modern data processing technologies like pySpark and Databricks to build, validate, and monitor data pipelines • Contribute to the broader Data Platform vision of making data discoverable, trustworthy, and actionable across Addepar

Role Description Join the Global Cloud Services organization's FinOps Tools team, which is building ServiceNow's next-generation analytics and financial governance platform. As the Distinguished Engineer for the FinOps Engineering Platform, you will set and own the technical vision and architecture for the entire platform. - Own the end-to-end technical architecture of the FinOps Engineering Platform. - Lead the design and development of the GCS Data Warehouse and the program to migrate ServiceNow's Global Cloud Services data platform off Cloudera onto the modern lakehouse. - Set the technical vision and multi-year roadmap for the platform. - Make the highest-leverage, hardest-to-reverse technical decisions. - Establish platform-wide engineering standards for reliability, determinism, observability, security, and production readiness. - Drive innovation across the platform, including the responsible use of AI/ML tooling. - Foster a culture of engineering craftsmanship, knowledge-sharing, and thoughtful quality practices. - Move fast while protecting the architectural integrity that lets it scale. Qualifications - Experience in leveraging or critically thinking about how to integrate AI into work processes. - 15+ years of experience in software or data engineering. - Proven track record as the lead architect or top technical authority for a platform. - Proven experience leading a large data platform migration or modernization. - Deep expertise across the modern data stack and in distributed-systems and cloud-native architecture. - Strong systems and backend engineering depth. - Hands-on experience with cloud cost management and FinOps. - Demonstrated ability to operate at high velocity in greenfield environments. - Strong knowledge of data structures, algorithms, and software quality principles. - Full professional proficiency in English. Requirements - Platform architecture: Designing and owning the architecture of large, multi-component platforms. - Modern data stack & lakehouse: Trino/Presto, dbt, Apache Iceberg, Lightdash. - Platform migration & modernization: Migrating off legacy Hadoop/Cloudera onto a modern lakehouse. - Forecasting & simulation: Deterministic, reproducible computation, multi-period simulation. - Cloud capacity & reservations: Hyperscaler capacity procurement. - Multi-cloud & infrastructure: Kubernetes, Infrastructure as Code, CI/CD. - Reliability & observability: SLI/SLO/error-budget design. - Data contracts & quality: Fail-loud ingestion and correctness invariants. - API & integration design: RESTful services and webhook/event integrations. Benefits - Base pay of $221,200 - $387,100, plus equity and variable/incentive compensation. - Health plans, including flexible spending accounts. - 401(k) Plan with company match. - ESPP and matching donations. - Flexible time away plan and family leave programs.