data-engineer
Data pipelines and analytics infrastructure
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Data pipelines and analytics infrastructure
Master data engineering, ETL/ELT, data warehousing, SQL optimization, and analytics. Use when building data pipelines, designing data systems, or working with large datasets.
PostgreSQL streaming replication - setup, monitoring, failover
Scale PostgreSQL - partitioning, connection pooling, high availability
Master machine learning, data engineering, AI engineering, MLOps, and prompt engineering. Build intelligent systems from data pipelines to production AI applications with LLMs, agents, and modern frameworks.
Write efficient resolvers with DataLoader, batching, and N+1 prevention
Database integration - schema design, queries, migrations, optimization
Master dimensional data modeling including star schema design, slowly changing dimensions, fact tables, and data warehouse architecture
Bulk insert optimization pattern for static/reference data sync
Create, run, and manage Domino Jobs - batch executions for scripts, training, and data processing. Covers job configuration, hardware tiers, scheduled jobs (cron), monitoring status, viewing logs, and API-drive...
Work with Domino Datasets - high-performance, versioned filesystem storage. Covers dataset creation, snapshots for versioning, sharing across projects, mounting paths (/domino/datasets/), and performance optimi...
Connect Domino workloads to external data sources including AWS S3 (via Mountpoint CSI driver), credential propagation with AWS IRSA and Azure Entra ID, and External Data Volumes. Use when configuring S3 access...
Work with distributed computing frameworks in Domino including Apache Spark, Ray, and Dask clusters. Covers cluster configuration, on-demand clusters, choosing between frameworks, PySpark usage, and scaling wor...
Use the domino-data Python SDK (dominodatalab-data) for programmatic data access in Domino. Covers DataSourceClient for SQL queries and object storage, DatasetClient for dataset files, TrainingSets for ML data...
Create Domino Launchers - parameterized web forms for self-service job execution. Enable business users to run analyses, generate reports, and trigger batch predictions without coding. Covers parameter types, e...
Orchestrate multi-step ML workflows using Domino Flows (built on Flyte). Define DAGs with typed inputs/outputs, heterogeneous environments, automatic lineage, and reproducibility. Use when building data pipelin...
Processes CSV files and pandas DataFrames. Use when working with CSV files, tabular data, spreadsheets, or when the user asks to query, analyze, or manipulate structured data.
Store ClickHouse Cloud credentials in Doppler + 1Password for gapless-crypto-clickhouse. Use when setting up new services, rotating credentials, or backing up authentication material. Covers API keys, connectio...
Test and validate ClickHouse Cloud connection using clickhouse-connect for gapless-crypto-clickhouse. Use when validating connectivity, troubleshooting connection issues, or verifying environment configuration....
Install, configure, and validate local ClickHouse for gapless-crypto-clickhouse development and backtesting. Use when setting up local development environment, enabling offline mode, improving query performance...
Fetch ClickHouse Cloud service details from API (organization ID, service endpoints, configuration). Use when setting up new ClickHouse Cloud services, discovering endpoints, or validating service metadata for...
Onboard company employees (Claude Code CLI users) to use gapless-crypto-clickhouse package with ClickHouse Cloud credentials. Use when company employee needs to set up ClickHouse Cloud access, mentions first-ti...
PostgreSQL database optimization combining institutional knowledge with live analysis
WHEN: SQL query review, query optimization, index usage, N+1 detection, performance analysis WHAT: Query plan analysis + Index recommendations + N+1 detection + Join optimization + Performance tuning WHEN NOT:...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.