Senior Data Integration Engineer

16 000 – 26 000 $

≈ 1,4 млн–2,3 млн ₽

🏢 ОфисMiddleПолная занятостьРелокация

16 000 – 26 000 $≈ 1,4 млн–2,3 млн ₽

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Наша компания

We are looking for a Data Integration Engineer to take ownership of our data streams end-to-end. In this role, your primary focus isn't traditional UI or API testing—you will dive deep into the data itself. You will act as the vital link between raw incoming data feeds and a high-quality final product, ensuring accuracy, consistency, and reliability across our entire data pipeline. If you care about data as a product and want to solve complex data anomalies at their source, we’d love to talk!

Чем предстоит заниматься

Data Quality Ownership: Define data quality requirements, metrics, and SLAs aligned with business and engineering needs

Monitoring & Alerting: Set up dashboards, track data SLAs, and proactively identify anomalies, drift, duplicates, and defects within numerical and production data streams

Incident Investigation & Remediation (RCA): Conduct root cause analysis across the full data lifecycle when discrepancies occur, fix incorrect records, and implement measures to prevent recurrence

Integration & Schema Design: Participate in designing data schemas/models and lead the onboarding and ingestion of new data sources and APIs

Automation & Coverage: Expand automated data quality test coverage and build pipeline checks to catch issues early

Cross-Functional Collaboration: Partner closely with developers, product managers, and analysts to clarify requirements, optimize pipelines, and drive quality improvements

Documentation: Maintain and evolve comprehensive data documentation, schema definitions, and defect logs

Наши требования

Experience in finance or trading domain

Familiarity with TradingView as a product

Scripting & Automation: Python skills for writing data processing scripts or automated quality checks, or proficiency with Regex for searching large data arrays

Advanced Data Stack: Experience with streaming platforms (e.g., Kafka), data observability tools, or data catalogs and metadata manag

2+ years in Data Engineering, Data Quality, DataOps, or Data Analytics

Core Data Quality Skills: Strong understanding of data profiling, data anomalies, and core DQ dimensions (completeness, accuracy, consistency, timeliness)

Technical & Pipeline Expertise: Hands-on experience with data pipelines (ETL, batch, or streaming) and data feed ingestion through APIs and backend services

CLI & Linux: High comfort level working in the terminal (Bash / Linux command line) and reading application logs

Developer Workflows: Solid knowledge of JSON/YAML, version control (Git/GitHub), CI/CD practices (e.g., GitLab, Jenkins), and general SDLC concepts

Language Skills: English proficiency (B2+ or strong reading and written technical communication)

TradingView

Georgia

ГрейдMiddle

ЗанятостьПолная занятость

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Опубликовано1 авг.

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