Data Scientist / Analytics Engineer

As a Data Integration Engineer, you will leverage technical skills, analytical insights, and business acumen to ensure accurate and complete data integration for feeding data science models. You will play a critical role in supporting new and existing clients, ensuring optimal performance, and managing the data processes for some of the largest eCommerce merchants globally. Our clients come from diverse industries, using various technical platforms, and each presents unique data challenges and order flows that require tailored solutions. The team focuses on scoping, implementing, validating, and monitoring data integrations from both technical and business perspectives. - Conducting due diligence on merchant websites, business models, and data flows. - Developing tailored data templates (JSON, CSV) to guide merchant developers and data teams in creating high-quality online (API) and offline (file transfer) integrations. - Writing queries and scripts (R, Python, SQL, Spark, Databricks) to: - Test, validate, and troubleshoot data issues in API calls across sandbox and production environments. - Test, validate, transform, and upload large historical data files via APIs. - Managing the data configuration layer of the platform, including automated tagging, transformation, and filtering. - Performing ad hoc data wrangling and sanitization tasks. - Monitoring automated data alerts and managing data irregularities by coordinating with internal and external stakeholders. - Collaborating with analysts, research teams, and data scientists to adapt to industry data changes. - Identifying and proposing system-wide solutions for common data issues. - Partnering with client-facing teams to engage with customers regarding their data integrations. - Supporting R&D, Product Management, Data Science, Integrations Engineering, Account Management, and Sales teams as a subject matter expert. Qualification Required: - 5+ years of experience in a data-centric role (Analytics, Data Engineering, ETL, DBA, Consulting, etc.). - 3+ years of experience working with SQL or NoSQL databases. - 3+ years of experience in data wrangling (using R or Python). - 3+ years of experience optimizing technical processes. As a Data Integration Engineer, you will leverage technical skills, analytical insights, and business acumen to ensure accurate and complete data integration for feeding data science models. You will play a critical role in supporting new and existing clients, ensuring optimal performance, and managing the data processes for some of the largest eCommerce merchants globally. Our clients come from diverse industries, using various technical platforms, and each presents unique data challenges and order flows that require tailored solutions. The team focuses on scoping, implementing, validating, and monitoring data integrations from both technical and business perspectives. - Conducting due diligence on merchant websites, business models, and data flows. - Developing tailored data templates (JSON, CSV) to guide merchant developers and data teams in creating high-quality online (API) and offline (file transfer) integrations. - Writing queries and scripts (R, Python, SQL, Spark, Databricks) to: - Test, validate, and troubleshoot data issues in API calls across sandbox and production environments. - Test, validate, transform, and upload large historical data files via APIs. - Managing the data configuration layer of the platform, including automated tagging, transformation, and filtering. - Performing ad hoc data wrangling and sanitization tasks. - Monitoring automated data alerts and managing data irregularities by coordinating with internal and external stakeholders. - Collaborating with analysts, research teams, and data scientists to adapt to industry data changes. - Identifying and proposing system-wide solutions for common data issues. - Partnering with client-facing teams to engage with customers regarding their data integrations. - Supporting R&D, Product Management, Data Science, Integrations Engineering, Account Management, and Sales teams as a subject matter expert. Qualification Required: - 5+ years of experience in a data-centric role (Analytics, Data Engineering, ETL, DBA, Consulting, etc.). - 3+ years of experience working with SQL or NoSQL databases. - 3+ years of experience in data wrangling (using R or Python). - 3+ years of experience optimizing technical processes.