• Collaboratively refine and evangelize a comprehensive framework for integrating data-thinking into the software development lifecycle for product teams • Design, architect, and maintain core marketplace datasets, data marts, and feature stores that support a blend of mature products and features with a rapidly evolving product line, in partnership with analytics, data science, and machine learning • Integrate with teams consisting of product engineers, analysts, data scientists, machine learning engineers throughout Thumbtack to understand their data needs, and help design datasets with the same engineering rigor as any other software we design • Drive data quality and best practices across different business areas • Help build the next generation data products at Thumbtack, based on real-time data products on top of Apache Kafka

• Maintain and update static master data directly in Salesforce using Data Loader, Data Import Wizard, and other native tools. • Work with business data owners and SMEs to identify all required source data across various systems. • Analyse source structures and map fields, relationships, and reference data to Salesforce objects. • Lead data cleansing with stakeholders to remove duplicates, standardize values, populate missing mandatory fields, and correct inconsistent or deprecated values. • Transform and prepare data based on agreed mapping logic and cleansing rules. • Execute or support test data loads in SIT and UAT. • Monitor data quality through dashboards, reports, and exception logs; drive continuous improvement. • Handle routine BAU data requests, updates, extracts, and reconciliations.

• Lead the technical conversion of SAS datasets, programs, and logic to SQL Server • Analyze existing SAS workflows and translate them into efficient SQL Server–based solutions • Design, implement, and optimize SQL Server schemas, stored procedures, views, and queries • Own SQL Server administration, including: Performance tuning and indexing, Security and access controls, and b ackup, recovery, and reliability practices • Validate data accuracy and performance against existing SAS outputs • Collaborate with technical and business stakeholders to ensure a successful migration • Document architecture, migration patterns, and operational procedures

• Design and deploy scalable Google Cloud services in GCP. • Implement IAM access controls to ensure secure and compliant data environments. • Develop and implement robust data ingestion pipelines from diverse sources. • Develop and enforce data validation processes to maintain accuracy and reliability. • Enhance data quality and efficiency through continuous optimization. • Analyze raw data to uncover patterns, trends, and opportunities. • Produce clear design documentation and solution roadmaps. • Lead projects independently while collaborating effectively within larger teams. • Mentor and cross‑train junior and senior Data Engineers, sharing expertise on complex assignments. • Advance your skills through hands‑on experience and formal learning opportunities. • Support pre‑sales activities by providing accurate work estimates and technical input. • Partner closely with Project Management to deliver projects on time and within budget. • Travel occasionally as required for project or team needs.