Data Engineering Copilot
Tekris Labs · tekrislabs.com
Design, build, debug, recover and optimize dependable data pipelines and platforms. Work across Apache Spark, Databricks, Delta Lake, structured streaming, CDC, orchestration, dbt, SQL warehouses, Microsoft Fabric/OneLake, data quality, lineage and incident response. Inspect actual code, logs, query plans and data contracts where the user supplies them or authorized tools are available; identify root causes, plan safe replay and backfills, check schema/row grain, and validate fixes. Includes multi-agent coordination guidance when genuine subagent tools exist. Skills-only: no automatic access to clusters, credentials, datasets or production systems; executions and changes require enabled tools and permissions.
How to install Data Engineering Copilot in ChatGPT
- Open the official listing for Data Engineering Copilot in the ChatGPT workspace you want to use.
- Choose Install plugin if available. Follow any connection steps for the apps listed on the page.
- Open a new conversation on a supported ChatGPT surface. Select Data Engineering Copilot from the plugin options or mention it by name.
How to use Data Engineering Copilot
Check the marketplace listing or publisher’s documentation for supported actions and examples.
Ranking history
Browse the order shown in the public ChatGPT Plugins directory on each capture date. Popular is a curated collection. OpenAI does not publish install or usage counts here.
Frequently asked questions
Why is Install plugin missing?
Check your account, workspace, plan and region. If the listing says Desktop only, open it in the ChatGPT desktop app.
Capabilities
- Architect batch
- CDC
- streaming
- lakehouse and warehouse data systems
- Debug duplicates
- data loss
- latency
- failures and stale pipelines from evidence
- Plan safe backfills
- replay
- checkpoint recovery and rollback strategies
- Review CDC merge ordering
- delete propagation and idempotent writes
- Diagnose Spark and Databricks query plans
- shuffle
- skew
- spill and file layout
- Design Microsoft Fabric Lakehouse
- OneLake
- shortcuts and deployment flows
- Design dbt/SQL transformations
- model grain
- incremental updates and contracts
- Review Airflow orchestration
- retries
- scheduling and backfill safety
- Build data quality
- freshness
- reconciliation and observability checks
- Assess access control
- governance
- PII handling and data lineage
- Coordinate supported specialist agents and evidence-based verification
- Prepare version-aware implementation plans and release/incident evidenceShow more