Marionete is an independently minded, entrepreneurial technology consultancy helping clients exploit tomorrow's technology to find unexpected solutions to today's business problems.
Key Responsibilities:We would welcome applicants who have a deep technical knowledge and hands-on experience of designing and implementing data architectures with practical knowledge of the Databricks ecosystem from data ingestion to governance to ML Ops.
Additionally, knowledge of Kafka would be useful.
Required Skills:Strong experience in streaming applicationsExperience with the Databricks ecosystem: LakeHouse, DatabricksIQ, ML-Flow, DataOps, MLOps, Ray, ModelOps, LLMOps, Unity Catalogue, Spark, Photon, Parquet, Delta-LakeFamiliarity with Kanban / Agile / Scrum methodologiesPreferred Skills:Modern data warehouseWorkflow automation tools e.g.
Airflow, TalendExperience in a recognised consultancyBackground in Banking, Financial Services, or InsurancePersonal Attributes:You will have a consultative, collaborative approach to team working and may be already working at a recognised consultancy.
You will be an articulate communicator, able to take complex problems and summarise them for a non-technical audience.
Benefits:Competitive compensationBenefits package, including health insurance and mental health supportFinancial support for ongoing trainingRelaxed dress code at the Marionete officesAn abundance of career paths and opportunities in which to advanceA flexible and hybrid work environmentMarionete believes in providing equal employment opportunities to everyone.
We do not practice and will not tolerate discrimination on the basis of race, skin color, ethnicity, national origin, gender, sexual orientation, marital status, maternity, religion, age, disability, gender identity, results of genetic testing, or service in the military.
By applying to Marionete vacancies, you agree that your data and CV remain secure and confidential with your application.
Marionete is a company in compliance with General Data Protection Regulation (GDPR).
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