You will get a market data health check for gaps, duplicates and OHLC issues
Project details
I will audit your market data for gaps, duplicate records, OHLC integrity issues, timestamp inconsistencies, symbol mapping problems, and other data quality risks.
This service is designed for financial data platforms, trading systems, analytics products, and historical market datasets using PostgreSQL, TimescaleDB, MySQL, or MS SQL Server.
You will receive:
• A structured audit summary
• Key findings with severity classification
• Up to 8 reusable SQL validation queries
• Prioritized recommendations
• Guidance on next implementation steps
The audit can cover OHLCV and related financial datasets such as fundamentals, earnings, and corporate actions.
I can work with read-only database access, database exports, or representative CSV/Parquet datasets.
Important: this is an audit and diagnostic service. Data repair, implementation, ETL redevelopment, migrations, and production changes are not included and can be scoped separately.
I am the Founder & Lead Engineer of Monolitics and built the data infrastructure behind Metravise, processing 40M+ market records.
This service is designed for financial data platforms, trading systems, analytics products, and historical market datasets using PostgreSQL, TimescaleDB, MySQL, or MS SQL Server.
You will receive:
• A structured audit summary
• Key findings with severity classification
• Up to 8 reusable SQL validation queries
• Prioritized recommendations
• Guidance on next implementation steps
The audit can cover OHLCV and related financial datasets such as fundamentals, earnings, and corporate actions.
I can work with read-only database access, database exports, or representative CSV/Parquet datasets.
Important: this is an audit and diagnostic service. Data repair, implementation, ETL redevelopment, migrations, and production changes are not included and can be scoped separately.
I am the Founder & Lead Engineer of Monolitics and built the data infrastructure behind Metravise, processing 40M+ market records.
Database Type
MySQL, MS SQL, PostgreSQLWhat's included $350
These options are included with the project scope.
$350
- Delivery Time 2 days
- Number of Revisions 1
- Number of Queries 8
- Query Analysis
- Source Code
Frequently asked questions
About Bahadir
Financial Data Infrastructure | ETL, APIs & PostgreSQL
Antalya, Turkey - 6:02 am local time
My focus is market data ingestion, ETL pipelines, PostgreSQL/TimescaleDB architectures, financial APIs, and backend systems that need to handle large volumes of structured market data reliably.
I am the Founder & Lead Engineer of Monolitics and the architect behind Metravise, a production-ready US stocks market intelligence platform.
Through Metravise, I designed and built:
• 40M+ continuously growing market records
• 10 domain-level ETL pipelines
• ~20 extraction workflows
• 61 REST API endpoints
• 42 Cron Jobs and 2 Worker Services
• 78 database tables and 21 views
• Financial data processing across OHLCV, fundamentals, earnings, news, technical indicators, picks, verdicts, and notifications
I can help with:
• Financial data platform architecture
• Market data provider integrations
• ETL pipelines, backfill, and incremental sync
• PostgreSQL / TimescaleDB data modeling
• Financial REST APIs
• Data quality audits
• Backend assessment and modernization
I work primarily on fixed-scope projects with clear deliverables, timelines, and boundaries.
Core stack:
Python • TypeScript • SQL • PostgreSQL • TimescaleDB • Pandas • REST APIs • ETL • Docker
Steps for completing your project
After purchasing the project, send requirements so Bahadir can start the project.
Delivery time starts when Bahadir receives requirements from you.
Bahadir works on your project following the steps below.
Revisions may occur after the delivery date.
Scope and access review
I review your requirements, data access method, database structure, and audit priorities.
Data quality analysis
I run checks for gaps, duplicates, OHLC inconsistencies, timestamp issues, symbol mapping problems, and related data quality risks.