Data Engineering Copilot
ChatGPT pluginBuild reliable data pipelines
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.
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Movement
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Rank in Data & analytics
6 listing changes logged · latest Nov 3: Capabilities, Description, Skills and 3 more. See what changed
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How this plugin compares with others in the same category. Positions are counted within the category, not across the whole directory.
Data & analytics272nd of 650 by placement
| # | Plugin | Position | 7d |
|---|---|---|---|
| 270 | #5441 | 79places down | |
| 271 | #5445 | 90places up | |
| 272 | #5514 | 76places down | |
| 273 | #5524 | 64places down | |
| 274 | #5538 | 45places up |
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12 more on the publisher’s page.
Example prompts
- “Diagnose this failing or incorrect pipeline using logs, code and data-quality evidence.”
- “Design a reliable CDC or lakehouse pipeline with replay, recovery and data contracts.”
- “Plan a safe backfill and validation strategy while live ingestion continues.”
Skills
build-data-pipeline
Implement or improve a SQL, Python, PySpark or orchestration pipeline with version-aware safe writes and test evidence.
data-engineering
Route data engineering design, debugging, implementation, recovery, observability, optimization, and security requests to focused skills.
debug-data-pipeline
Diagnose failing, duplicated, stale, late or incorrect data pipelines using job logs, sample data and execution evidence.
design-cdc-pipeline
Design source-to-target change data capture with authoritative ordering, deletes, schema evolution and idempotent MERGE.
design-data-quality
Design source/target data contracts, reconciliation, completeness, freshness and anomaly tests with actions.
design-fabric-lakehouse
Design or diagnose Microsoft Fabric Lakehouse, OneLake, data pipelines, shortcuts and deployment workflows.
design-orchestration
Design Airflow or other job orchestration with idempotent retries, scheduling, dependencies and safe backfills.
design-streaming
Design and troubleshoot Structured Streaming sources, state, watermarking, checkpoints and sink semantics.
design-warehouse-dbt
Design dbt and SQL warehouse incremental models, tests, snapshots, lineage and release gates.
modernize-data-platform
Migrate legacy ETL, Spark, schedulers, cloud warehouses or lakehouse code while preserving correctness and contracts.
observe-data-platform
Define data-platform operational telemetry, SLOs, alerting and cost drivers tied to recovery decisions.
orchestrate-data-agents
Coordinate actual specialist agents for complex data engineering tasks only when supported execution tools exist.
Show all 18Show fewer
plan-backfill-replay
Plan safe historical backfills, CDC replays and checkpoint recovery without duplicates or lost data.
plan-data-platform
Architect batch, CDC, streaming, lakehouse or warehouse data systems with correctness, access, SLA and recovery trade-offs.
respond-data-incident
Triage an active production data incident and plan containment, evidence capture, safe recovery, and stakeholder updates.
review-data-model
Review SQL data-model grain, key uniqueness, fact/dimension joins, slowly changing dimensions and metric definitions.
secure-data-platform
Review data-pipeline permissions, secrets, PII, tenant isolation, lineage, retention and audit boundaries.
tune-spark-databricks
Diagnose Spark and Databricks performance using actual plans, stage metrics, skew, spill and storage layout evidence.
- Categories
- Made by
- Tekris Labs · Website
- Sign-in
- On Install
- 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 evidence
- Availability
- Available
- Version
- 0.2.0
- Keywords
- data-engineering, spark, databricks, delta-lake, fabric, onelake, airflow, dbt, cdc, streaming, data-quality
- Created
- September 23, 2026
- More info
- Sponsorship
- Promote this plugin