• Completing migration of last legacy MySQL data to Databricks platform • Building and maintaining data pipelines using Databricks, Fivetran, DBT, and Airflow • Handling data engineering tasks: ingestion, reliability, performance • Assisting in cleanly phasing out legacy systems • Collaborating with senior team, picking up tasks independently

Role Description We are seeking a Senior Data Engineer to support core marketplace analytics data products and platform work. This role will focus on building and maintaining reliable data pipelines, Snowflake data models, dbt transformations, and observability practices that support analytics, reporting, and business decision-making. Enterprise experience strongly preferred. Key Responsibilities - Build and optimize scalable data pipelines using Python and dbt. - Design and maintain Snowflake warehouse structures, database tables, and performant data models. - Develop reliable ETL/ELT workflows for extracting, transforming, loading, and validating data from multiple sources. - Maintain data quality and consistency across analytics and reporting workflows. - Improve pipeline reliability through monitoring, data observability, troubleshooting, and proactive issue resolution. - Support reporting and dashboard needs that provide actionable insights for business stakeholders. - Collaborate cross-functionally to clarify requirements, communicate progress, and ensure transparency across initiatives. Qualifications - Strong SQL skills for querying, transforming, validating, and optimizing data. - Python experience for scalable data pipelines, automation scripts, and data processing workflows. - Hands-on Snowflake experience designing and maintaining warehouse structures, tables, and data models. - dbt experience developing modular transformations, tests, and documentation within modern ELT workflows. - AWS familiarity for scalable data storage, processing, and pipeline orchestration. - Experience building reliable ETL/ELT workflows across multiple data sources. - Ability to monitor pipeline health, troubleshoot workflow issues, and improve data reliability and quality. - Strong communication skills and ability to partner cross-functionally with technical and business stakeholders. Requirements - Dagster or similar orchestration experience. - Experience supporting marketplace, hiring, performance, or business analytics data products. - Dashboarding or reporting experience for business-facing analytics. Benefits - Remote contract role. - LATAM-based candidates only. - Must be able to work with meaningful overlap with U.S. business hours. - 40 hours per week. - Contract currently expected to run through September 30, 2026.

• Lead, mentor, and manage a team of Power BI and Power Platform developers, including task allocation and performance oversight. • Ensure all development work is effectively scoped, prioritised, monitored, and delivered on time and to a high standard. • Own the reporting and analytics function, partnering with stakeholders to gather requirements and define KPIs aligned to business objectives. • Oversee the design, development, and maintenance of Power BI reports, dashboards, and semantic data models. • Develop and optimise SQL queries, stored procedures, and database objects within Azure SQL and SQL Server environments. • Manage the administration of Azure SQL databases, including performance tuning, security, access control, and troubleshooting. • Design, develop, and support solutions within Microsoft Fabric, including Lakehouses and Notebooks. • Support and enhance ETL processes and broader data integration workflows. • Identify and drive improvements in reporting capability, data quality, and platform performance. • Establish and maintain documentation, standards, and knowledge-sharing practices across the data platform and reporting ecosystem. • Explore and promote the use of data and AI to enhance reporting, automate processes, and unlock greater organisational insight.

• Design, develop, and maintain scalable ETL and ELT pipelines. • Build and optimize data architectures, databases, and data warehouses. • Integrate data from multiple sources, APIs, and third-party platforms. • Ensure data quality, consistency, reliability, and security. • Monitor and troubleshoot data pipelines and workflows. • Collaborate with analytics, engineering, and business teams to understand data requirements. • Implement data governance and best practices for data management. • Optimize data storage, processing performance, and query efficiency. • Support reporting, business intelligence, and analytics initiatives. • Document data models, workflows, and technical processes.