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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Databricks Engineer with Genie - **Company:** Capgemini - **Location:** Harrisburg, PA, United States - **Salary:** $86,549.0 - $135,221.0 - **Contract:** Temporary contract - **Skills:** Adobe Analytics, Google AdWords, Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Code Review, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Security, DevOps, Email Production, Google Analytics, Apache Hive, Job Scheduling, Python (Programming Language), Automation of Marketing, Marketing Information Systems, Metadata, Performance Tuning, Scrum Methodology, Power BI, Standard Sql, Salesforce.Com, Software Deployment, Data Streaming, Tableau (Software), Web Analytics, Web Traffics, Enterprise Data Management, Azure Data Factory, Apache Spark, Eloqua, Git, Data Lakes, Pyspark, Information Technology, Marketo, AWS Data Analytics, Machine Learning Operations, Restful APIs, Data Pipelines, Databricks - **Published:** August 4, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=c37120edd193930a ## About the Role * Azure * AWS * GCP, * Strong communication skills. * Ability to work directly with Marketing business teams. * Excellent analytical and problem-solving skills. * Ability to work independently. * Strong documentation skills. * Experience working in Agile teams. Education: Bachelor's or Master's degree in: * Computer Science * Information Technology * Data Engineering * Related Engineering discipline Preferred Certifications: * Databricks Certified Data Engineer Associate * Databricks Certified Data Engineer Professional * Azure Data Engineer Associate (Preferred) * AWS Data Analytics Specialty (Preferred) ## Description ETL/ELT Development marketing analytics marketo Power BI DevOps & CI/CD REST APIs integration Marketing Platforms PySpark/Python, TE Connectivity is seeking an experienced Databricks Data Engineer with hands-on experience in Databricks Genie (AI/BI) to build scalable marketing data products and enable conversational analytics. The engineer will design and develop robust data pipelines, curate trusted marketing datasets, and implement Genie-enabled semantic models that allow business users to explore marketing data using natural language. Genie provides governed natural-language access to enterprise data through curated business definitions and Unity Catalog governance., * Design, develop, and optimize scalable ETL/ELT pipelines using Databricks. * Build Bronze, Silver, and Gold layer data products following Medallion Architecture. * Develop data ingestion pipelines from CRM, Marketing Automation, Digital Marketing, Web Analytics, and ERP systems. * Create reusable Delta Live Tables (DLT) and workflow orchestration using Databricks Workflows. * Implement data quality, validation, reconciliation, and monitoring processes. * Optimize Spark jobs for performance and cost efficiency. * Build dimensional models for Marketing Analytics. * Develop AI/BI Dashboards for business users. * Configure and maintain Databricks Genie Agents (formerly Genie Spaces) for Marketing domain analytics. * Curate business terminology, metrics, sample questions, and semantic definitions for Genie. * Collaborate with Marketing stakeholders to translate business requirements into trusted analytical assets. * Configure Unity Catalog permissions and ensure secure data access. * Support production deployments, incident resolution, and continuous improvements. * Participate in Agile ceremonies, sprint planning, and code reviews. Required Technical Skills: Databricks: * Databricks Workspace * Delta Lake * Unity Catalog * Delta Live Tables (DLT) * Databricks Workflows * Auto Loader * Structured Streaming * Databricks Asset Bundles (preferred) * Performance Optimization * Job Scheduling Data Engineering: * PySpark * Spark SQL * Python * SQL * Data Modeling * ETL/ELT Development * Data Quality Frameworks * Git * CI/CD, * Salesforce CRM * Adobe Analytics * Google Analytics * Marketo * Eloqua * Google Ads * LinkedIn Campaign Manager * Email Marketing Platforms * Customer Journey Analytics Databricks Genie Experience (Mandatory): * + Hands-on experience implementing Databricks Genie Agents for business users. * + Configure Genie knowledge stores, business definitions, and semantic metadata. * + Create trusted metrics and reusable business terminology. * + Build natural language analytics experiences for Marketing users. * + Improve Genie response accuracy using sample questions, business rules, joins, and semantic descriptions. * + Support AI-powered dashboards integrated with Genie for self-service analytics. Genie uses curated metadata, business rules, * and Unity Catalog-governed assets to answer natural-language business questions. Marketing Analytics Experience: Experience supporting reporting and analytics for: * Campaign Performance * Lead Funnel Analytics * Customer Acquisition * Marketing Attribution * ROI Analysis * Digital Marketing Performance * Customer Segmentation * Pipeline Analytics * Email Campaign Analytics * Website Traffic Analytics Nice to Have: * Power BI * Tableau * dbt * MLflow * AI/ML exposure * Lakehouse Architecture * REST APIs * Marketing Mix Modeling * Customer 360 * CDP Platforms, * Production-grade Databricks pipelines * Marketing Gold Layer datasets * AI-ready semantic models * Genie Agent configuration * Trusted business metrics * Marketing dashboards * Automated data quality framework * Technical documentation * Production support and optimization ## Related Videos - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Got AI ideas but no money? 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