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Builds and maintains an enterprise-scale data platform using Databricks, Snowflake, and Microsoft Fabric, focusing on automation, Kubernetes, and cloud-native DevOps to enable self-service analytics and operational excellence.
Lead the architecture of an enterprise data platform spanning ingestion, storage, processing, governance, and consumption layers, using tools like Snowflake, Databricks, Spark, Kafka, and modern lakehouse formats.
Define and lead the architecture of an enterprise data platform (ingestion, storage, processing, governance, consumption) using tools like Snowflake, Databricks, Spark, and Kafka, partnering with engineering, ML, and business stakeholders.
Design, develop, and maintain scalable data pipelines and platforms using Databricks, Delta Lake, SQL, Java, and Python for a Fortune 10 healthcare company.
The Senior Data Architect will lead the migration of legacy Microsoft BI and WPS data warehouse systems to a modern Databricks Lakehouse architecture on AWS. This role involves defining data strategy, establishing governance standards, and ensuring scalable, secure data management across the organization.
The Lead Data Engineer will design, develop, and optimize enterprise-scale ETL/ELT pipelines and data processing solutions using Azure technologies like Synapse, Databricks, and Spark. The role involves leading technical initiatives, mentoring team members, and ensuring data quality and platform reliability.
Senior Data Engineer building scalable data platforms, ETL/ELT pipelines, and data lakes on Azure and AWS using PySpark, Databricks, and Apache Spark.
Design, develop, and maintain scalable ETL data pipelines on Databricks and Azure, integrating diverse data sources to support analytics, reporting, and ML while ensuring governance and reliability.
Data Scientist building end-to-end ML models and production data pipelines in Databricks (Python, PySpark, SQL) to power hyper-personalized CRM campaigns, churn reduction, and CLV prediction for a retail beauty company.
Full Stack Data Engineer owning the end-to-end data lifecycle on Databricks/AWS with Power BI reporting, driving data democratisation and AI-first workflows in a hybrid Warsaw role.
The Data Scientist will build and deploy predictive models and data pipelines in Databricks to drive customer lifetime value and personalization strategies. This role involves end-to-end ownership of machine learning projects, from feature engineering to production monitoring, while collaborating with marketing and CRM teams.
Senior Data Engineer on the Commerce Team building and maintaining production-grade ETL/data pipelines using Python, PySpark, and Databricks to support streaming service monetization at Warner Bros. Discovery in Hyderabad.
Designs and oversees a modern, enterprise-scale data platform for TD’s Global Transaction Banking, focusing on real-time pipelines, AI-ready foundations, and data products. Defines architecture for data ingestion, processing (Spark/Flink), storage, governance, and APIs while ensuring scalability, cost optimization, and regulatory compliance.
Hands-on Data Architect designing and evolving a Databricks/AWS lakehouse data platform for healthcare clients, leading architecture reviews, data governance, and mentoring engineers.
Senior Software Engineer on the Data Platform team building data governance systems (privacy, security, metadata, compliance) for an AI productivity platform processing 70B+ events/day, using Spark, lakehouse/warehouse technologies like Databricks, Delta Lake, dbt, and Snowflake.
Designs, builds, and maintains data pipelines, integrations, and platform capabilities for Malibu Boats, bridging SQL-based systems with Microsoft Fabric. Focuses on modernizing legacy ETL, supporting production integrations, and ensuring data reliability across business applications, manufacturing, and analytics.
Lead the architecture and management of enterprise-scale cloud-native data platforms using Databricks, AWS, Terraform, and dbt to support Asset Management analytics, reporting, and compliance functions.
Lead the design and operation of scalable data pipelines that ingest, process, and deliver multimodal training data for AI models, ensuring quality and reliability for model development.
Lead Databricks/Spark engineer responsible for configuring data lakes, optimizing pipelines, and training clients on cloud data solutions. Core focus: Spark, Databricks, and distributed data architectures.
Data Scientist role centered on the Databricks ecosystem (Lakehouse, Delta Lake, Unity Catalog, Lakeflow, Lakebase) combined with AI/ML, GenAI, RAG, LLMs, LangChain, LangGraph, Agentic AI, and FastAPI/REST API development.
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