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Build and maintain the AI platform and data lakehouse, automating operations and integrating services with APIs and cloud infrastructure using Python, Kubernetes, and MLOps tools.
Design modern data architectures and cloud strategies for financial institutions, leading teams to implement scalable analytics, governance, and AI solutions.
Builds and maintains scalable blockchain data platforms for a DeFi exchange, using big-data tools like Hadoop and Hive to analyze on-chain and trading data.
Build and own a large-scale Web3 big data platform that ingests on-chain transactions, trading behavior, and user profiles, then layer AI/ML tools for fraud detection, risk modeling, and natural-language data querying.
Senior Data Engineer builds and maintains scalable data pipelines and infrastructure using AWS, Databricks, and Kafka to support analytics and AI initiatives in a large media company.
Lead a team to maintain and enhance an Azure-based data platform, building ETL pipelines and ensuring data quality for real-estate analytics and products.
Lead a team to build and maintain ETL pipelines, Azure Data Platform, and data storage infrastructure using PySpark, Python, SQL, and Azure Databricks.
Build backend services for real-time fraud detection and risk analysis using Java/Spring Boot, Kafka, and AI-assisted tools.
Build AI-powered data platform tools (React UIs, Python APIs, vector stores) that let users explore and query financial data in natural language while ensuring security and correctness in a regulated environment.
Design and implement AWS-based data and AI platforms for APAC clients, ensuring scalable, compliant solutions that drive business outcomes.
Design and optimize Apache Hive SQL-based data warehouse solutions on Hadoop, tuning queries and managing data partitioning for enterprise-scale integrity.
Builds and maintains big-data pipelines and APIs using Python, Spark, Kafka, Hadoop, and SQL to process and analyze large datasets for IBM clients.
Designs and builds scalable data infrastructure and ETL pipelines using Python, Java, SQL, and cloud tools to support analytics and ML.
Builds and maintains scalable data pipelines and infrastructure using Python, SQL, and cloud services to support analytics and machine learning workflows.
Designs and builds data pipelines, ETL processes, and streaming ingestion using Spark, Kafka, and cloud tools to feed analytics platforms.
Lead a team to build and optimize scalable data pipelines using Snowflake, Databricks, and Kafka, ensuring security, governance, and performance for a global fast-food company.
Designs and builds data pipelines to ingest, process, and store structured and unstructured data using cloud and on-prem tools like Spark, Kafka, and HDFS.
Build and maintain scalable data pipelines and cloud infrastructure (GCP/AWS/Azure) to process large datasets, using SQL and Python for ETL and data quality monitoring.
Build and maintain scalable data pipelines and infrastructure to collect, process, and analyze data for an iGaming company using Java/Scala, SQL/NoSQL, and Spark.
Designs and builds scalable big-data infrastructure and ETL pipelines using Python, Spark, and cloud services to support reporting and analytics.
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