“data engineering”

Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure.

Data engineering for batch and streaming pipelines with Airflow, dbt, Spark, and Kafka.

World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, real-time streaming, and data infrastructure.

Data engineering workflows for designing reliable pipelines and datasets: ingestion, transforms, orchestration, schema evolution, data contracts, quality…

World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure.

Use for AI and agent engineering work: system prompt design, tool call architecture, context engineering, memory and learning systems, multi-agent…

Analytics engineering across data modeling, dbt, transformation, and semantic layers.

Data and Database Engineer expert in schema design, query optimization, and data pipelines.

Design and build use cases, POCs and production systems with TypeSafe's Jev decision model (System One): choose a design mode and a use-case archetype, build…

Expert analytics engineering covering data modeling, dbt development, data transformation, and semantic layer management.

A comprehensive collection of Agent Skills for context engineering, harness engineering, multi-agent architectures, and production agent systems.

Use when answering org-level or repo-level GitHub maintenance questions about repository inventory, branch health, PR backlog, or safe cleanup follow-up.

Your software-engineering brain trust.

Feature construction from market data for ML trading models including price, volume, on-chain, and microstructure features

Use when preparing a medical-imaging dataset (DICOM/NIfTI) for modelling.

ICM-based zero-to-verified engineering workflow.

Master context engineering for AI agent systems.

Collect immutable, timestamped ICAIRE LinkedIn and X post-level snapshots when refreshing Audience Growth Engine source data.

Chaos engineering: hypothesis-driven fault injection to surface weakness before users do.

Analyzes and engineers protein glycosylation by scanning canonical N-glycosylation sequons, describing S/T-rich regions, checking curated glycan evidence, and…

Run bounded, evidence-driven loops for repeated, resumable, delegated, or scheduled work.

Rigorous agentic engineering workflow — 23 playbooks and 23 principle rules for bug fixes, features, refactors, performance work, investigations, architecture…

Principal Go Engineer skill providing cloud-native, high-performance, resilient, observable, and idiomatic Go backend services and distributed systems.

Curates the right context for an agent at the right time.