обновлено 1 день назад
Senior Data Integration Engineer (QA)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Integration Engineer (QA) (Data Quality and Integration): Ensuring the accuracy, consistency, and reliability of financial data streams across the full data pipeline with an accent on data quality metrics, anomaly detection, schema design, and automated coverage. Focus on investigating root causes across the data lifecycle, onboarding new data sources and APIs, and preventing recurring defects in numerical and production data.
Location: Hybrid in Tbilisi or Limassol
Company
is a financial analysis platform providing charting, market data, collaboration, and publishing tools to users worldwide.
What you will do
- Define data quality requirements, metrics, and service-level agreements aligned with business and engineering needs.
- Build dashboards, monitor data SLAs, and identify anomalies, drift, duplicates, and defects in numerical and production data streams.
- Investigate incidents through root cause analysis across the full data lifecycle, correct inaccurate records, and prevent recurrence.
- Design data schemas and models, and lead the onboarding and ingestion of new data sources and APIs.
- Expand automated data quality test coverage and implement pipeline checks for early defect detection.
- Collaborate with developers, product managers, and analysts while maintaining data documentation, schema definitions, and defect logs.
Requirements
- 2+ years of experience in data integration, data quality, DataOps, or data analytics.
- Strong understanding of data profiling, anomalies, and data quality dimensions including completeness, accuracy, consistency, and timeliness.
- Hands-on experience with ETL, batch, or streaming pipelines and data-feed ingestion through APIs and backend services.
- Knowledge of JSON, YAML, Git/GitHub, CI/CD practices, and general SDLC concepts.
- English proficiency at B2 level or higher, including strong written and technical reading skills.
- Domain knowledge in investments, brokerage, crypto exchanges, or financial markets.
Nice to have
- Python scripting for data processing or automated quality checks, or Regex experience with large data arrays.
- Experience with Kafka or other streaming platforms, data observability tools, data catalogs, or metadata management.
- Familiarity with AI tools and AI-assisted engineering workflows.
- Strong command of Bash, Linux command-line tools, and application logs.
- Familiarity with as a product.
Culture & Benefits
- Flexible working hours and a hybrid work format.
- Well-equipped offices for focused and collaborative work.
- Learning, mentorship, and long-term career growth opportunities.
- Relocation support and private health insurance.
- Performance-based bonuses, Premium access, and regular team events and company-wide meetups.
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