Tag: #data-engineering
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 26 posts
Data Engineering Complete Guide 2025: Flink vs Spark, dbt, Iceberg, Airflow — Modern Data Stack Deep Dive
Flink vs Spark stream processing comparison, dbt crossing $100M ARR, Iceberg vs Delta Lake vs Hudi lakehouse showdown, ClickHouse vs StarRocks real-time analytics, Airflow 3.0 vs Dagster vs Prefect orchestration — the co
2026-03-22 · 30 min read #data-engineering#apache-flink#apache-spark#dbt#apache-icebergToss Bank Data Engineer (Kafka & Streaming) Study Guide: Tech Stack, Interview Prep, and 6-Month Roadmap
Complete analysis of Toss Bank Real-Time Data team JD. Master Kafka Broker operations, Spring Boot Kafka Client, Active-Active replication, CDC with Debezium, Flink stream processing, and ClickHouse analytics — with a 6-
2026-03-21 · 29 min read #kafka#data-engineering#tossbank#streaming#flinkApache Spark in Production: Performance Tuning, Shuffle, Skew, AQE, and Streaming Operations
A practical production guide to Apache Spark covering the execution model that matters, shuffle and skew, AQE, cache strategy, and Structured Streaming operational checklists.
2026-03-17 · 6 min read #spark#spark-tuning#data-engineering#shuffle#adaptive-query-executionData Engineering & AI Pipeline Guide: From Apache Spark to Kafka
A comprehensive guide to data engineering for AI. Covers Apache Spark, Kafka, Airflow, dbt, Delta Lake, and Feature Stores for designing and implementing large-scale data pipelines.
2026-03-17 · 12 min read #data-engineering#apache-spark#kafka#airflow#dbtDuckDB In-Memory Analytics and OLAP Guide
A guide to DuckDB in-memory analytics for OLAP workloads, covering query optimization, data formats, and integration patterns.
2026-03-15 · 28 min read #database#duckdb#olap#analytics#in-memoryMLOps Feature Store in Practice — Building a Feature Pipeline with Feast
Build an offline/online feature store with Feast and create a production-grade pipeline that serves consistent features for both training and serving
2026-03-02 · 9 min read #mlops#feast#feature-store#machine-learning#data-engineering