{"id":2173010,"url":"https://alion.io/job/keep-simple-senior-data-engineer-databricks-ai-platforms","title":"Senior Data Engineer (Databricks & AI Platforms)","company":{"id":2593999,"name":"Keep Simple","domain":"keepsimple.io","url":"https://alion.io/company/keepsimple","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Gupy","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["São Bernardo do Campo, Brazil"],"countries":["BR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":46000,"max_usd":120000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2127},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Feature Store","optional":true},{"name":"Hugging Face","optional":true},{"name":"LangChain","optional":true},{"name":"MLFlow","optional":true},{"name":"OpenAI","optional":true},{"name":"Semantic Kernel","optional":true}],"status":"live","first_seen_at":"2026-10-09T12:48:07Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-11T20:09:08Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Come work for a large global financial and insurance products company! This is your chance !!\nStart a successful career in a renowned company in the international market! Great opportunity!\nGlobal insurance and asset management company seeks a responsible, organized, dynamic and team-oriented person.\nResponsabilidades e atribuições\nThe Senior Data Engineer is responsible for designing, building, and optimizing scalable data platforms and pipelines that support analytics, business intelligence, machine learning (ML), and AI-driven solutions.\nThis role partners with data scientists, AI engineers, architects, and business stakeholders to deliver trusted, high-quality data products using Databricks, cloud technologies, and modern data engineering practices. The position also serves as a technical leader in enabling enterprise AI and Generative AI initiatives through robust, secure, and governed data platforms.\nKey Responsibilities:\nDesign, develop, and maintain scalable data pipelines and data products using Databricks, Spark, Python, and SQL;\nBuild and optimize batch, streaming, and real-time data integration solutions from enterprise and third-party data sources;\nImplement Databricks Lakehouse architectures utilizing Delta Lake and Medallion design patterns;\nDevelop and maintain data products that support analytics, predictive modeling, machine learning, and Generative AI applications;\nCollaborate with Data Scientists and AI Engineers to prepare, transform, and govern data for AI and ML use cases;\nDesign and implement feature engineering pipelines and support ML lifecycle processes;\nDevelop data solutions that support Retrieval Augmented Generation (RAG), vector search, semantic search, and LLM-based applications;\nOptimize Spark jobs, SQL workloads, and data processing frameworks for performance, scalability, and cost efficiency;\nImplement data quality, observability, lineage, governance, and monitoring capabilities;\nEnsure compliance with data privacy, security, and responsible AI standards;\nContribute to CI/CD, Infrastructure-as-Code, and DataOps practices across the data platform;\nMentor junior engineers and promote engineering best practices across the organization.\nRequisitos e qualificações\nRequired Qualifications:\nBachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field;\n7+ years of experience in data engineering, ETL development, or large-scale data platform engineering;\n3+ years of hands-on experience with Databricks and Apache Spark;\nStrong proficiency in Python, SQL, and distributed data processing frameworks;\nExperience building cloud-based data lakes, data warehouses, and Lakehouse architectures;\nExperience supporting AI, machine learning, or advanced analytics initiatives;\nStrong understanding of data modeling, data governance, and enterprise data management practices;\nExperience developing and optimizing large-scale data pipelines in AWS, Azure, or Google Cloud.\nPreferred Qualifications:\nExperience with Databricks Delta Lake, Unity Catalog, Delta Live Tables, MLflow, Mosaic AI, and Databricks Workflows;\nHands-on experience supporting Generative AI, Large Language Models (LLMs), RAG architectures, vector databases, or AI-powered applications;\nFamiliarity with AI frameworks such as LangChain, Semantic Kernel, OpenAI APIs, Hugging Face, or similar technologies;\nExperience with feature stores, model training pipelines, and machine learning operationalization (MLOps);\nExperience with Kafka, Event Hub, or other streaming technologies;\nDatabricks Certified Data Engineer Professional or equivalent cloud certification.\n\nKey Competencies:\nDatabricks Platform Engineering;\nApache Spark Development;\nAI & Machine Learning Data Engineering;\nGenerative AI Data Solutions;\nLakehouse Architecture;\nData Modeling & Data Warehousing;\nData Governance & Security;\nData Observability & Reliability Engineering;\nCloud Data Platforms (AWS/Azure);\nDataOps, CI/CD & Automation;\nTechnical Leadership & Mentoring.\nSuccess Measures:\nDelivery of scalable, reliable, and secure data platforms supporting analytics, AI, and business operations;\nSuccessful enablement of AI and Generative AI use cases through high-quality, governed data products;\nImproved data quality, pipeline reliability, and platform performance;\nIncreased automation, operational efficiency, and reuse of engineering frameworks;\nAdoption of data engineering standards and best practices across development teams;\nMeasurable improvements in AI/ML solution delivery speed and business value realization.\nInformações adicionais\nModelo de contratação:\nPJ.\nForma de atuação:\nHíbrido (3x por semana presencial no escritório de Pinheiros/SP).","description_format":"text","description_chars":4703,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Brazil","iso":"BR","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Personal Development","Coaching & Mentoring"],"lifecycle":[{"event":"open","at":"2026-10-09T13:02:35Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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