data-engineer
Specialized data engineering agent for designing ETL/ELT pipelines, defining data schemas, managing data quality, and implementing robust ingestion workflows.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
107 skills found
Specialized data engineering agent for designing ETL/ELT pipelines, defining data schemas, managing data quality, and implementing robust ingestion workflows.
Migrate standard PostgreSQL tables to TimescaleDB hypertables with optimized partitioning, chunking, and compression strategies for time-series data.
Generates data cleaning pipelines for pandas/polars/PySpark, handling missing values, duplicates, outliers, type conversions, and validation.
A modular data processing tool for cleaning, validating, and analyzing CSV files with support for custom transformations and automated dependency management.
A multi-paradigm ETL pipeline agent supporting batch and streaming data processing, schema inference, and configurable DAG-based transformations for heterogeneous data sources.
Create, manage, and debug dlt (data load tool) pipelines for ingesting data from APIs, databases, and custom sources into destinations like DuckDB, BigQuery, and Snowflake.
Data Analysis Specialist for EDA, statistical modeling, SQL queries, and Python-based visualization. Turn raw datasets into actionable insights through rigorous quantitative methods.
Manage dlt data pipelines and Temporal workflows for the SignalRoom marketing platform. Sync sources like Everflow, Redtrack, and S3 to Postgres, check status, and debug ingestion.
Convert natural language queries to safe, optimized SQL. Automates database interactions with schema awareness and parameterized query generation.
Load, validate, and preprocess weekly insurance policy CSV data with intelligent period detection and standardization.
World-class senior data engineering skill for building scalable data pipelines, ETL/ELT systems, and modern data infrastructure using Python, Spark, dbt, and Kafka.
Database schema validation, data integrity testing, migration validation, transaction isolation, and query performance testing. Ensure ACID compliance and referential integrity for data-driven applications.