Location:
Remote (Europe time-zone overlap preferred)
About the Client
Our client is a
specialized investment firm
that merges market expertise with advanced data intelligence. They focus on identifying early signals and sentiment shifts across social and digital ecosystems to inform high-impact trading strategies. Operating at the intersection of finance, technology, and media analytics, they value data precision, innovation, and speed-to-insight. The firm cultivates a fast-paced, intellectually curious environment where data engineers and market experts collaborate closely to turn unstructured information into actionable signals.
About the Role
We're seeking a
Data Engineer
to lead data acquisition, structuring, and interpretation across social and web-native platforms such as X/Twitter, Reddit, TikTok, YouTube, and Telegram. You'll build pipelines that transform noisy, real-time data into market-relevant insights—helping traders anticipate sentiment shifts and virality trends.
This role is hands-on and highly collaborative, requiring both technical rigor and curiosity about human behavior online.
Key Responsibilities
- Acquire, clean, and maintain data streams from social media APIs and third-party brokers.
- Build entity and ticker extraction pipelines that interpret slang, misspellings, and symbols accurately.
- Generate sentiment, virality, and acceleration metrics that predict market movements.
- Ensure data quality through precision/recall tracking and source validation.
- Collaborate with traders, quants, and other engineers to iterate quickly on production-ready tools and dashboards.
Qualifications & Experience
- 3–6+ years in data engineering, analytics, or applied data roles (social, alt-data, or market intelligence).
- Strong command of
Python and SQL
; proficient in handling large and messy datasets. - Familiar with
social APIs
,
NLP techniques
, and data ingestion best practices. - Good grasp of
statistical validation
, including backtests and bias control. - Excellent communication—able to turn complex data evidence into concise insights.
Preferred:
- Experience with financial data, time-series, or influence graph modeling.
- Knowledge of modern data formats (Parquet, Delta, Iceberg) and fast query engines (DuckDB, ClickHouse, BigQuery).
- Familiarity with light multimodal data processing (ASR, OCR, video metadata).
Success Metrics
- Improved signal-to-noise ratio across social data feeds.
- Accurate, early detection of market-relevant sentiment and virality.
- Efficient, reproducible data pipelines with measurable lift in trading performance.
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