Senior Data Engineer

Skip to main contentThis website uses cookies to improve your web experience. By using the site, you agree to the use of cookies. Privacy PolicyDeclineAccept CookiesEnglishSign InSenior Data Engineer page is loadedSenior Data EngineerApplyremote typeHybridlocationsLisbon, PortugalRemote, Portugaltime typeFull timeposted onPosted 7 Days Agojob requisition idR35183Job DescriptionAbout usWe are looking for a Senior Data Engineer to support the Foundation Insights team. You will work cross-functionally to help drive analytics, enablement, and data-driven decision-making for our global engineering and product teams. Foundation Insights at Zendesk owns operational data for Engineering and Product Development — measuring productivity, reliability, AI adoption, and infrastructure excellence.As a Senior Data Engineer, your role will be designing, building, testing, and maintaining highly scalable data pipelines and analytical data models. You will ensure that systems meet business requirements and industry practices, and you'll have the opportunity to work with many datasets and tools such as GitHub, Jira, Snowflake, dbt, and AI platforms like Claude and MCP servers, among others. Your responsibilities will include building dimensional models, integrating data sources, optimizing performance, and developing self-service data products. Your contributions will play a significant role in shaping our engineering data strategy and will directly impact decision-making capabilities throughout all of Product Development.What you'll do:Design and build dimensional data models using dbt in SnowflakeDevelop and maintain ETL pipelines and Airflow DAGs to centralize engineering operational metrics across multiple Snowflake accountsBuild self-service data products including Django-based dashboards, MCP servers for AI-powered data exploration, and interactive analytics applicationsBuild data models to track platform adoption, AI tool usage, and ROI across engineering.Optimize data product performance through query optimization, pre-aggregated models, and caching strategies to improve dashboard and API response timesImplement data quality tests, monitoring, and validation layers to ensure accuracy and prevent invalid metric comparisonsIntegrate data from APIs and third-party tools into Snowflake for analytics and AI enrichmentUse best engineering practices such as CI/CD, infrastructure-as-code, code review, comprehensive testing, and documentationCollaborate with Engineering, Product, and leadership to measure infrastructure adoption, AI ROI, and engineering productivityWhat you bring to the role:Basic Qualifications:3-5+ years of data engineering experience building, maintaining, and optimizing production data pipelines and analytical data modelsProven proficiency in Python and SQL — comfortable with complex queries, ETL development, and application development (Django/Flask)Hands-on dbt experience — building dimensional models, writing tests, managing dependencies, and optimizing performanceExperience with cloud data warehouses (Ex. Snowflake, BigQuery, Redshift, Databricks) including query optimization and cost managementInternally motivated, self-starter with strong analytical thinking — you dig into data anomalies and ask "why" until you understand root causesAbility to work cross-functionally and communicate technical concepts to both engineers and non-technical stakeholdersDetail-oriented with a passion for data quality, testing, and building reliable production systemsPreferred Qualifications:Data orchestration with Airflow — building DAGs, managing dependencies, and monitoring pipeline healthProficiency in infrastructure-as-code practices, particularly using Terraform for managing Snowflake and cloud resourcesWeb development with Django, Flask, or similar Python frameworks for building data applicationsLLM/AI integration experience — working with Claude, GPT, or other AI APIs; building MCP servers or AI agent frameworksExperience integrating...