“data engineering”

Expert data engineer specializing in building reliable data pipelines, lakehouse architectures, and scalable data infrastructure with ETL/ELT, Apache Spark…

Use for ingestion, ETL or ELT, data pipelines, mapping, cleansing, validation, reconciliation, lineage, warehousing, dimensional models, semantic layers, file…

Data quality verification skill for data engineering tasks.

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.

Specialist subagent: ETL pipelines, data warehousing, stream processing, and data infrastructure specialist.

BigQuery medallion architecture (bronze/silver/gold), parameterized queries, MERGE upserts, partitioning, CDC dedup, Temporal orchestration.

MCP server for data engineering: validation, transformation, visualization, and APIs.

Read-only NPRA pharmaceutical records and pipeline health for Malaysia (5 tools).

MCP runtime copilot for health checks, regressions, explainability, and operational memory.

Extracts logic from UI/rendering, enforcing a data-driven architecture.

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

Make an engineering drawing of a part as a PDF - orthographic views with hidden lines and centre marks, real dimensions, hole callouts, notes and a title…

Guide engineering design and implementation decisions.

Analytics engineering - dbt projects, maintainable SQL as CTE pipelines, event patterns (funnels, sessions, retention, window functions, MATCH_RECOGNIZE).

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

Break down complex bioinformatics, data engineering, and algorithmic pipelines from first principles.

Resolve complex literal requirements, data semantics, provenance, and acceptance against the production engineering workflow.

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…

Hire a specialist consultant (architect, security-auditor, business-analyst, performance-reviewer, refactor-critic, api-designer, data-engineer, qa-reviewer)…

Write, rewrite, and polish LinkedIn posts for technical AI, benchmark, privacy, data, engineering, research, product, and open-source updates.

Also use for agentic data engineering pipelines, code generation agents, agent-powered CLI tools, MCP server development, or any system where an AI model…

Route durable data modeling, analytics engineering, and data-science analysis; not for model-training systems or generic application architecture.

Guides audio mastering for streaming platforms including loudness optimization and tonal balance.