{"id":1841614,"url":"https://alion.io/job/zurich-australia-data-engineer-databricks","title":"Data Engineer - Databricks","company":{"id":1943356,"name":"Zurich Australia","domain":"zurich.com.au","url":"https://alion.io/company/zurich-com-au","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Mexico City, Mexico"],"countries":["MX"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":89000,"max_usd":171000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":352},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Airflow","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"Azure DevOps","optional":true},{"name":"Delta Lake","optional":true},{"name":"LLM","optional":true},{"name":"MLFlow","optional":true}],"status":"live","first_seen_at":"2026-09-14T02:00:00Z","employer_posted_date":"2026-09-14","last_verified_at":"2026-10-07T01:04:18Z","board_verified":true,"closed_at":null,"days_open":22,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":22},"description":"#ZCC\nZurich Capability Center is currently hiring a:\nData Engineer - Databricks\nResponsibilities\nAs a Data Engineer, your main tasks will involve:\nDesign, build, and maintain scalable data pipelines using Databricks and cloud-based data platforms.\nDevelop, optimize, and automate ETL/ELT processes to support analytics, reporting, and machine learning initiatives.\nWork closely with Data Scientists, Analysts, ML Engineers, and business stakeholders to understand data requirements and deliver reliable datasets.\nImplement data ingestion frameworks from multiple structured and unstructured data sources.\nBuild and maintain data models, data lakes, and data warehouses that support enterprise analytics needs.\nEnsure data quality, consistency, governance, and security across platforms.\nOptimize Spark workloads and Databricks environments for performance and cost efficiency.\nSupport deployment and operationalization of machine learning solutions by providing production-ready datasets and feature pipelines.\nCollaborate with Azure, IT, and DevOps teams to implement CI/CD and DataOps best practices.\nMonitor, troubleshoot, and continuously improve data platform performance and reliability.\nYour Skills and Experience\nAs a Data Engineer, your skills and experience will ideally include:\nRequired\nBachelor's Degree in Computer Science, Engineering, Information Systems, Mathematics, or a related field.\n3+ years of experience in Data Engineering, Data Warehousing, or Big Data environments.\nStrong programming skills in Python and SQL.\nHands-on experience with Databricks, Apache Spark, and distributed data processing.\nExperience designing and developing ETL/ELT data pipelines.\nExperience working with Data Lakes and modern data architectures.\nUnderstanding of data modeling concepts including Star Schema and Dimensional Modeling.\nExperience working with Git and version control systems.\nStrong analytical and problem-solving skills.\nEnglish level B2 or higher.\nPreferred Qualifications\nExperience with Azure Data Platform services, including: \nAzure Databricks\nAzure Data Factory\nAzure Data Lake Storage\nAzure Synapse Analytics\nAzure DevOps\nExperience working with Delta Lake and Lakehouse architecture.\nKnowledge of orchestration tools such as Airflow, Databricks Workflows, or Azure Data Factory.\nExperience supporting Machine Learning use cases and MLOps practices.\nFamiliarity with MLflow and model deployment processes.\nKnowledge of CI/CD, Infrastructure as Code, and DataOps practices.\nExperience with streaming technologies such as Kafka or Event Hubs.\nExperience working in Agile environments.\nInsurance industry experience is a plus.\nNice to Have\nExperience collaborating with Data Science teams and supporting AI/ML initiatives.\nKnowledge of Generative AI, LLM data pipelines, vector databases, and embedding workflows.\nExperience with Unity Catalog, data governance, and metadata management.\nExposure to cloud-native architectures and enterprise-scale data platforms.\n\nIf you are interested, please apply directly through this link or send your resume to .\nPosition available only for candidates located in Mexico City, State of Mexico, or Guadalajara. Please apply only if you reside in one of these areas.\nWho we are\nLooking for a challenging and inspiring work environment where you can make a difference? At Zurich millions of individuals and businesses place their trust in our products and services every day. Our 53,000 employees worldwide form the basis of our success, enabling, businesses and communities to face a world of risk with confidence. Imagine if you could help people do this all over the world. You’d give them confidence and reassurance by protecting what they love most. It’s a big challenge, but you will be supported by a world-class team who believe in helping you to reach your full potential and deliver on our promises.\nSo be challenged. Be inspired. Help us make a difference.\nAt Zurich we are an equal opportunity employer. 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