The AI kit for Data Engineers

Designs your full pipeline: sources, transforms, orchestration, and data quality checks, for example a daily orders load into Snowflake.

Builds a repeatable extract, transform, load flow, for example pulling finance CSV exports into your warehouse each morning.

Finds why a query is slow, proposes index or rewrite changes, and verifies results match on real data.

Writes production Airflow DAGs with retries, sensors, and tests, for example a backfillable hourly ingestion job.

Like "Generate Python Data Transformation Script"

Like "Write Data Quality Test Cases"

Like "Design ETL Pipeline Architecture"

Like "Diagnose a Pipeline Failure from Logs"

Datasets that are valid and safe to publish.

Bordereaux that pass schema and reconcile to control totals.

Migrations rehearsed safely with schema and data intact.

Pipelines adapt to upstream changes without corrupting data.

Lets your AI check Apache Airflow DAGs, runs, and task logs, and trigger or clear runs when you allow it.

Lets your AI check your data for errors, explain what went wrong, and suggest SQL fixes.

Let your AI check and manage Debezium and Kafka Connect data connectors for you.

Lets your AI check and manage your Apache Airflow workflows for you, right from the chat.

Ascend.io: Otto automates building, monitoring and repairing data pipelines, detects schema changes, resolves failures and maintains pipeline health so teams de

Tinybird Code is a CLI agent with deep ClickHouse expertise, enabling you to build, deploy, and optimize real-time data pipelines efficiently—from concept to pr

Context Data automates ETL development and scheduling for startups and enterprises building Generative AI, reducing setup time from two weeks to under 10 minute

SmartScripter is an AI-powered tool that crafts custom scripts in languages like Python, SQL, and JavaScript to automate repetitive tasks. Ideal for professiona

Build this to track pipeline requests, owners, and freshness reviews in one place instead of scattered tickets.

Build this to draft SQL against your real schema and repair broken queries before they hit production.

Build this to reuse source prep steps and keep rights, lineage, and review notes attached to each raw feed.

Connect schema drift to documented consumers.

Designs and builds scalable data pipelines, warehouses, and streaming architectures for reliable analytics infrastructure.

Design and implement scalable batch and streaming data pipelines

Build production Airflow DAGs with operators, sensors, testing, and deployment patterns. No cron job replacements. No non-Airflow orchestration. No pr

Organize dbt models into staging, intermediate, and marts with tests, docs, and incremental builds.