Senior Software Developer — Historical Data Store

CompatibL, a leading provider of trading and risk management software solutions, is looking for a talented Python Developer with a good level of English (B2+) to join its growing team.

About the role

You will build the Historical Data Store: a Python-based framework for sourcing historical market data, running data quality controls, and filling gaps in time series. The framework uses XiNG to abstract algorithms, so a core part of the job is designing clean abstraction layers — pluggable sourcing adapters, configurable quality rules, and interchangeable filling/proxying algorithms — rather than one-off pipelines. The data you produce feeds HVaR and P&L attribution downstream, so correctness and auditability are first-class requirements.

Responsibilities

• Design and build the sourcing layer: adapters for internal and vendor market data feeds, snap/alignment logic, versioned storage of historical time series.
• Implement the data quality framework: staleness detection, outlier/spike detection, cross-source consistency checks, coverage monitoring, exception workflows with full audit trail.
• Implement the data-filling framework: interpolation, forward/backward filling, proxy construction, and statistical filling methods — exposed as interchangeable algorithms via the XiNG abstraction layer.
• Design the algorithm abstraction: clear interfaces so quants and risk users can register, configure, and compose algorithms without touching framework internals.
• Ensure lineage and reproducibility: every filled or adjusted data point traceable to source, rule, and algorithm version (regulatory audit requirement).
• Partner with the risk calculation (ACE) team as the primary consumer, and with quants who define filling/proxying methodologies.

Must-have skills

• Python (expert): 7+ years of professional engineering with deep Python expertise — pandas/numpy at scale, typing, packaging, performance profiling; experience designing frameworks/libraries used by other teams, not just applications.
• Time-series data engineering: Large-scale historical market or sensor data — columnar storage (Parquet/Arrow), partitioning strategies, efficient range queries, versioning/bitemporal concepts.
• Data quality: Hands-on experience building validation/DQ frameworks: rule engines, anomaly detection on time series, monitoring and alerting on data pipelines.
• API and abstraction design: Demonstrated ability to design plugin architectures / strategy-pattern algorithm registries with clean, stable interfaces and good documentation.
• Engineering practice: Testing of data pipelines (property-based and regression testing on datasets), CI/CD, observability, production support.

Nice-to-have

• Market data domain knowledge: curves, surfaces, fixings, corporate actions, vendor feeds (Bloomberg BPIPE/SAPI, Refinitiv), snap conventions across time zones.
• Statistical gap-filling techniques: regression-based proxying, PCA-based reconstruction, EM-style imputation, backfill methodologies used for VaR history construction.
• Experience with orchestration tooling (Airflow/Dagster/Prefect) and data catalogs/lineage tooling.
• Exposure to risk platforms as data consumers (understanding what VaR/ES calculations need from historical data — e.g., 250+ day contiguous windows, stressed periods).
• Prior use of XiNG or comparable internal algorithm-abstraction frameworks.

Conditions of work, benefits and perks

• Full-time employment / cooperation with flexible working hours
• Comfy workplace in Warsaw or remote/hybrid option, of your choice
• Equipment: desktop computer/laptop, monitor(s), and office accessories
• Team-building events, company outings, and sport activities
• Internal training programs

Employment

• Up to 26 paid days of annual leave
• Annual bonus implemented after the end of the calendar year at the discretion of management basing on performance
• Private Luxmed medical care package
• Partial reimbursement for Medicover Sport package (coverage depends on selected plan)
• From partial to full reimbursement for training, conferences, and certifications based on certain criteria

Rewards and benefits for B2B cooperation are discussed and negotiated individually.