Data & Analytics

Modern Python development with Python 3.12+, Django, FastAPI, async patterns, and production best practices. Use for Python projects, APIs, data processing, or automation scripts.

Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.

Avoid common TensorFlow mistakes — tf.function retracing, GPU memory, data pipeline bottlenecks, and gradient traps.

Send transactional and marketing emails via SendGrid API. Supports templates, attachments, and email analytics.

Reconciles data sources using stable identifiers (Pay Number, driving licence, driver card, and driver qualification card numbers), producing exception reports and “no silent failure” checks. Use when you need weekly matching with explicit reasons for non-joins and mismatches.

Execute database migrations across ORMs and platforms with zero-downtime strategies, data transformation, and rollback procedures. Use when migrating databases, changing schemas, performing data transformations, or implementing zero-downtime deployment strategies.

Deploy privacy-first analytics with correct API patterns, rate limits, and GDPR compliance.

Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation, missing value handling, groupby operations, or performance optimization.

Implement Terraform Provider resources and data sources using the Plugin Framework. Use when developing CRUD operations, schema design, state management, and acceptance testing for provider resources.

Read, write, edit, and format Excel files (.xlsx). Create spreadsheets, manipulate data, apply formatting, manage sheets, merge cells, find/replace, and export to CSV/JSON/Markdown. Use for any Excel file manipulation task.

Query reading lists and book data from Hardcover.app via GraphQL API. Triggers when user mentions Hardcover, asks about their reading list/library, wants book progress, searches for books/authors/series, or references "currently reading", "want to read", or "books I've read". Also use for syncing reading data to other systems (Obsidian, etc.) or tracking reading goals.

Store and query time-series data with hypertables, compression, and continuous aggregates.