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Senior Data Engineer (f/m/d)
Build and maintain Azure Databricks pipelines and data models that power financial insights for global wind projects, collaborating with finance teams to deliver scalable data solutions.
Middle Data Engineer (Azure Databricks)
Builds and maintains cloud data pipelines using Azure Databricks, PySpark, and Delta Lake to power analytics and BI in a modern Lakehouse architecture.
Data Engineer
Build and maintain SOX-compliant Finance data pipelines and semantic models in Databricks and Power BI to deliver trusted, audit-ready data for Coty’s global reporting and analytics.
Azure Databricks Data Engineer – Lakehouse & Pipelines
Designs and builds Azure Databricks-based data pipelines and Lakehouse architectures using SQL Server, focusing on modern data infrastructure.
Software Engineer
Build and enhance a multi-dimensional indexing engine for Data Lakehouses using Java, Scala, and Rust, supporting open table formats like Iceberg.
Senior Data Engineer: Real-Time Retail Media & Forecasting
Build the real-time data backbone for a new adtech standard that turns physical retail shopper behavior into anonymized, measurable audiences using edge computing, streaming pipelines, and privacy-preserving AI.
Data Engineer
Build and scale ETL/ELT pipelines in PySpark and SQL, model enterprise data, and ensure quality and lineage for downstream analytics at a large IT consultancy.
Data Engineer
Design and build enterprise-scale data pipelines and warehouses to unify operational data for analytics and AI in Basel.
(Sr) Data Engineer Retail Media, Measure & Forecast
Build the data backbone for a new global Retail Media channel: transform raw sensor streams from thousands of stores into real-time measurement, forecasting, and attribution systems using Spark, Kafka, Trino, and privacy-preserving pipelines.
Databricks Data Engineer II: Pipelines & Lakehouse
Build and maintain scalable data pipelines on Databricks Lakehouse using Spark, Delta Lake, and orchestrators to deliver trusted datasets for analytics and AI.
Data Engineer Databricks
Builds scalable data pipelines and medallion architectures on Databricks and cloud platforms for clients, translating business needs into production-grade ELT/ETL solutions.
AVP Software Developer
Build and maintain Python/SQL backend services and data pipelines for a data-driven organisation, focusing on databases, ETL/ELT, and lakehouse architectures.
Senior Solutions Architect - Data & AI
Design and lead enterprise-scale data platforms and AI solutions on Azure, guiding clients from discovery to proposal while owning end-to-end architecture and pre-sales engagements.
Kafka Architect / Streaming Data Architect
Design and implement enterprise-scale Kafka streaming architectures for a bank’s data lakehouse, integrating Cloudera, Teradata, and Kafka Connect to enable real-time ingestion, processing, and reporting with high availability and governance.
Enterprise / Data Architect
Design and govern a large-scale data lakehouse and medallion architecture for a bank, ensuring alignment with enterprise models like FSLDM and regulatory standards.
Enterprise AI Architect: Data, MLOps & LLMs
Design and deliver enterprise-scale AI platforms, including data pipelines, MLOps, LLMs, and cloud-native solutions on AWS/Azure/GCP while ensuring compliance and mentoring teams.
IT Data Analyst
Builds Power BI dashboards and analyzes datasets to deliver business insights using SQL, DAX, and Microsoft Fabric, turning raw data into strategic decisions.
Lead Data Engineer: AI-Ready Lakehouse Architect
Lead the design and build of an AI-ready data lakehouse platform, integrating pipelines and distributed systems to support advanced analytics and compliance.
Principal Data-AI Engineering Architect
Principal architect leading enterprise-scale AI platforms, designing data pipelines, MLOps, LLMs, RAG, and cloud-native AI on AWS/Azure/GCP while ensuring compliance and scalability.
Data Modeler / Big Data Engineer
Designs and maintains scalable data models and architectures for a bank’s enterprise data platform using Cloudera, Hadoop, and Apache Iceberg.