3 of 3 Amazon Redshift Jobs in Central London

reconciliation checks Strong error handling, monitoring, and retry strategies in production pipelines Experience with incremental data processing patterns (CDC, watermarking, upserts) AWS Data Services Amazon S3: data lake architectures, partitioning strategies, lifecycle policies DynamoDB: data modeling, secondary indexes, streams, and performance optimization Amazon Redshift: foundational querying, integrations … performance considerations AWS Lambda for scalable data processing and orchestration Amazon EventBridge for event-driven and decoupled data pipelines Vector Databases & Embeddings Strong understanding of vector database concepts, indexing strategies, and performance trade-offs Design and implementation of embedding generation pipelines Optimization techniques for semantic search and retrieval accuracy ...

error handling and retry logic. Develop incremental data processing patterns for large-scale datasets. Work with AWS services including Glue, Step Functions, S3, DynamoDB, Redshift, Lambda, and EventBridge. Build and optimise vector database solutions and embedding generation pipelines for semantic search. Implement document processing workflows (PDF parsing, OCR, metadata ...

Skills: Analytical Tools: EDA, Data Mining, Visualization (Plotly, Matplotlib, Seaborn) Statistical & Multivariate Analysis Big Data: Hadoop, MapReduce, HDFS, DataBricks, Spark, PySpark DataLake Architecture, AWS Redshift, Kinesis, EMR Machine Learning Supervised Models: Nave Bayes, Logistic Regression, SVM, Linear Regression, KNN, Tree-Based Models: Decision Trees, Random Forest, Gradient Boosted Trees ...