SQL & Pipelines

Generate SQL queries from plain-English questions for BigQuery, Postgres and MySQL

Write graph queries in GQL or SQL/PGQ for paths, multi-hop traversal and reachability

Manage BigQuery datasets, tables and jobs and run SQL queries

Translate legacy Teradata, Oracle or Snowflake SQL and schemas to BigQuery GoogleSQL

Cut BigQuery cost with partitioning, clustering, editions and query tuning

Diagnose failing, slow or costly BigQuery jobs with step-by-step root-cause analysis

Create and troubleshoot BigQuery UDFs and remote functions in SQL, JavaScript or Python

Translate Snowflake dbt SQL models into BigQuery SQL with macros and types handled

Design a multi-cloud Iceberg data lakehouse with BigQuery data agents

Write and validate Apache Airflow DAGs for Managed Airflow on Google Cloud

Find why Managed Airflow DAG runs and task instances fail

Migrate Airflow DAGs to Airflow 2.11 or Airflow 3 with breaking-change scans

Tune and configure Managed Airflow environments for scale and cost

Check warehouse table freshness, row counts and schema drift every hour

Build Windmill data pipelines from scripts wired together with on and materialize

Write BigQuery queries as Windmill scripts with parameters

Write DuckDB queries as Windmill scripts for fast local analytics

Write MS SQL Server queries as Windmill scripts with parameters

Write MySQL queries as Windmill scripts with parameters

Write PostgreSQL queries as Windmill scripts with parameters

Write Snowflake queries as Windmill scripts with parameters

Build ETL pipelines with Spark, Airflow and dbt, plus data quality checks

Optimize SQL queries, design schemas and analyze data with SQL

Load SaaS data like HubSpot and Stripe into DuckDB for SQL analysis

Add business meaning, units and enum context to a Wren semantic project

Generate a Wren semantic MDL project by exploring a database schema

Onboard to Wren Engine, from environment checks to the first query

Query over 22 databases through the Wren CLI semantic SQL layer

Write and check PromQL, SQL and Doris log queries for Nightingale explorer panels

Generate SQL from natural language for MySQL, Doris, ClickHouse and PostgreSQL

Write Apache Spark jobs and tune shuffles, cluster settings and Spark SQL queries

Optimize slow SQL queries, write complex joins and window functions, and design schemas

Schema and business logic for tracking products, warehouses and stock levels

Schema and business logic for analyzing customers, orders and revenue data

Query MySQL databases and turn results into sales, user and business reports

Write dbt model SQL with reused fields, CTEs and joins that stay semantically correct

Open semantic-layer pull requests for dbt descriptions, AI hints and content migration

Answer business questions by writing and validating SQL against your warehouse

Build data pipelines with Airflow, Dagster, Kafka, Flink and dbt with quality checks

Optimize ClickHouse queries and analytics patterns for high-volume workloads

Turn plain questions into SQL and tune slow queries from their EXPLAIN plans

Query Auto Ontology over MCP or REST and check generated SQL and answers

Query databases and inspect schemas through the DBHub MCP server

Explore a database schema efficiently before writing SQL queries

Connect DBHub to a database and fix failing connection settings

Write correct, fast SQL for joins, aggregations, window functions and schema changes

Author and deploy Airflow DAGs and Serverless workflow files on AWS MWAA

Set up AWS Glue connections to JDBC databases, Redshift, Snowflake and BigQuery

Create managed Iceberg tables in S3 Tables with compaction and Glue registration