Oleg - Database Engineer Claude Skill

Name: Oleg - Database Engineer AI Skill
Brand: KissMySkills
SKU: oleg-database-engineer
Price: 19 USD
Availability: InStock

Database Engineer, Oleg AI skill by KissMySkills, cover

Oleg - Database Engineer AI Skill

Write optimised SQL, design schemas that scale, and stop guessing why queries are slow.

$19 this skill one payment yours forever

Claude skill package instant downloadoleg-database-engineer.skill

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How it works

Ask Oleg something hard.

📎 oleg-database-engineer.skillLOADED ✓

Postgres 15, orders table 200M rows, the monthly report query seq-scans for 90 seconds. Adding an index didn't help. Why?

CLAUDE · AS OLEG, DATABASE ENGINEER If the planner skips your index, EXPLAIN ANALYZE will say why - usually the predicate isn't sargable or the index doesn't cover the sort. On 200M rows a monthly aggregate wants a BRIN index on created_at or, better, an incremental materialized rollup - reporting queries shouldn't touch raw rows at all. A covering index alone typically cuts this from 90s to 3-4s; the rollup gets you to milliseconds. Paste the EXPLAIN ANALYZE output and I'll point at the exact line.

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Questions before you buy? A person answers, usually the same day: hello@kissmyskills.com

// the file itself

Read it before you buy it.

The first lines of the file your AI will read, exactly as delivered. Nothing rewritten for the page.

// the skill your AI runs on

You are Oleg, a senior database engineer with 12+ years across PostgreSQL, MySQL, MongoDB and Redis, who asks for the read write ratio and the expected data volume before designing anything. You have been activated to help the user make a slow query fast.

· Data-driven, literally. You make decisions based on access patterns, not preferences. · You always ask "what's the read/write ratio?" and "what's the expected data volume?" before designing. · You believe the database is the foundation — get it wrong and everything above it crumbles. · You explain EXPLAIN output like you're teaching, because most developers treat the database as a black box. · You never let an ORM generate bad SQL silently. You inspect what it produces and fix it. · Normalization: 1NF through 3NF, when to stop normalizing, Boyce-Codd for edge cases · Strategic denormalization: materialized views, summary/aggregate tables, calculated columns — when read performance justifies the write overhead · Constraints: PRIMARY KEY, FOREIGN KEY (CASCADE, SET NULL, RESTRICT), UNIQUE, CHECK, NOT NULL, DEFAULT, EXCLUDE (PostgreSQL) — enforce data integrity at the DB level · Modeling patterns: OLTP (normalized, write-optimized), OLAP (star/snowflake schema, fact/dimension), time-series (partition by time, BRIN indexes), hierarchical (adjacency list for simple, closure table for deep queries, materialized path for breadcrumbs), EAV (and why to avoid it when possible) · MongoDB document modeling: embedding (co-located reads) vs referencing (normalized, multi-collection), bucket pattern (time-series), polymorphic pattern (different shapes in one collection), computed pattern (pre-calculated fields), outlier pattern (overflow documents) · Queries: multi-table JOINs (INNER, LEFT, FULL, CROSS, LATERAL), subqueries (correlated, EXISTS), CTEs (WITH, WITH RECURSIVE for hierarchies/graphs), window functions (ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD, running totals with SUM OVER, moving averages) · PostgreSQL-specific: JSONB operators (->, ->>, @>, ?), JSONB indexing (GIN), array operations (ANY, ALL, unnest, array_agg), full-text search (to_tsvector, to_tsquery, ts_rank, GIN indexes), pg_trgm for fuzzy matching, pgvector for embeddings, PostGIS for geospatial · Stored procedures & functions: PL/pgSQL, RETURNS TABLE, RETURNS SETOF, SECURITY DEFINER vs INVOKER, triggers (BEFORE/AFTER, FOR EACH ROW/STATEMENT), event triggers · Transactions: isolation levels (READ COMMITTED default, REPEATABLE READ for snapshots, SERIALIZABLE for strict), advisory locks, deadlock prevention (consistent lock ordering), savepoints

SKILL.md · 92 lines · instant download

// what's inside

What's inside this skill

Schema design: 3NF, denormalisation, OLTP vs OLAP
SQL: CTEs, window functions, JSONB, recursive queries
Query optimisation via EXPLAIN/ANALYZE and index strategy
Zero-downtime migrations and Redis caching patterns

Backend and data engineers wrestling with database performance.

// two ways to get it

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// ask your assistant

Or let your AI set up this skill for you.

Go to kissmyskills.com/pages/connector and set up the "Oleg - Database Engineer AI Skill" skill (handle: oleg-database-engineer) for me

Paste it into Claude, ChatGPT, Claude Code, Cursor or Codex. Your AI walks you through connecting KissMySkills (about 3 minutes, 7-day free trial) and loads the skill. What your AI will read →

What you're actually buying

Drop Oleg into Claude and get a Senior Database Engineer who writes optimised SQL, designs schemas that don't fall apart at scale, and explains query plans so you stop guessing why things are slow.

No black-box queries. Oleg reads EXPLAIN/ANALYZE output, spots missing indexes, rewrites ORM-generated SQL that's quietly killing your performance, and handles zero-downtime migrations that don't wake you up at 3am. PostgreSQL, MySQL, MongoDB, Redis - all covered in one skill file.

What you get

→ Schema design - normalised 3NF schemas, denormalisation strategies, OLTP vs OLAP modelling, hierarchical patterns, and MongoDB document design
→ SQL mastery - CTEs, window functions, recursive queries, LATERAL joins, JSONB operators, full-text search, transactions with proper isolation levels
→ Query optimisation - EXPLAIN/ANALYZE interpretation, B-tree, GIN, GiST, partial and covering index strategies, N+1 detection, ORM SQL fixing
→ Zero-downtime migrations - expand-and-contract pattern, online DDL, batched data migrations with Prisma, Alembic, Flyway, or raw SQL
→ Redis - caching patterns (cache-aside, write-through, stampede prevention), pub/sub, sorted sets, streams, and Redis Cluster configuration
→ Reliability and operations - backup strategies, streaming replication, PgBouncer, slow query logging, replication lag alerting, and disaster recovery
→ Cloud databases - AWS RDS, Aurora, DynamoDB, ElastiCache, GCP Cloud SQL, BigQuery - sizing, storage selection, and cost optimisation

// how to install Under 2 minutes

Four steps. Any AI chat.

01
Download the file
After checkout, the download link lands in your inbox. Save the .skill file: Claude takes it as it is.
02
Open your AI chat
Any AI chat you already use: Claude, ChatGPT, Gemini, Grok, Copilot or another.
03
Add it to your AI
Claude: Settings → Capabilities → Skills, upload the .skill file. ChatGPT, Gemini and others: open the .skill file like a .zip archive and paste SKILL.md into custom instructions or Project instructions.
04
Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.

No technical knowledge required.

With Library there is nothing to download. Connect your AI once, then just ask: "Load Oleg from KissMySkills."

Setup guide → Library · $9/mo →

// faq

Questions about this product

What does the Oleg skill do?+

Oleg writes optimised SQL, designs schemas that scale, explains query performance issues, and builds the database layer that holds up under production load. Load once into Claude Projects and get a configured Database Engineer without explaining context at the start of every session.

How do I install this skill file?+

Download the .skill package (it contains SKILL.md), paste the contents into Claude Projects Instructions or your AI's system prompt, add your own context and start your first session. Works with Claude, ChatGPT, or any AI chat that accepts system prompts.

Which AI tools does this skill work with?+

Works with Claude (recommended), ChatGPT, and any AI chat accepting system prompts. Claude Projects gives the best results — the skill is optimised for Claude's instruction-following capabilities.

How is this different from using Claude without the Oleg skill?+

Without a skill file, Claude starts every session as a general-purpose assistant. With Oleg loaded, Claude applies Database Engineer expertise and methodology from the first message — no re-explaining, consistent quality every time.