Senior Python Developer

Description
Job Description:Senior Software Engineer Python (Computation & Rules Engine)Role OverviewWe are building a high-performance, deterministic computation engine in Python that executes complex, versioned rules and calculations over large, structured datasets. This engine powers financial availability, eligibility, and risk calculations and must be correct, explainable, auditable, and fast. Build a high-performance, deterministic Python computation engine that executes complex rules over large datasets with absolute correctness and explainability.This is a pure backend engineering role focused on algorithms, data processing, system design, and performancenot UI and not business analysis.Core Engineering ResponsibilitiesDesign and implement pure computation modules in Python with:Deterministic outputsIdempotent executionStrong guarantees around precision and reproducibilityBuild a rule execution framework supporting:Declarative rule definitionsVersioning and effective datingRule dependency graphsShort-circuiting and prioritizationImplement high-volume data pipelines to:Load, validate, normalize, and transform large datasetsExecute calculations efficiently in batch and incremental modesOptimize performance across:CPU usageMemory footprintIO patternsParallel execution (where appropriate)Design explainability artifacts:Structured calculation tracesRule evaluation graphsIntermediate state snapshotsImplement numerically safe calculations:Decimal arithmeticExplicit rounding strategiesStable aggregation and reconciliation logicBuild robust testing infrastructure:Unit tests for individual rulesProperty-based tests for invariantsGolden dataset regression testsDesign APIs and internal interfaces for:Batch executionStreaming / delta-based recalculationDownstream consumers (services, workflows)Required Technical SkillsStrong proficiency in Python (5+ years preferred)Deep experience with data-intensive systems, including:pandas / PolarsNumPyPyArrowSQL-backed pipelinesStrong understanding of:Algorithmic complexityMemory-efficient data structuresVectorized vs row-based execution tradeoffsExperience building:Rules enginesCalculation enginesCompilers / interpreters / evaluatorsSolid grasp of:Deterministic system designIdempotencyFault-tolerant batch processingStrong testing discipline, including:pytestProperty-based testing (Hypothesis)Reconciliation and diff-based validationPreferred / Advanced Engineering ExperienceDesigning DSLs or configuration-driven execution enginesWorking with large datasets (10M+ rows) or wide schemasParallel and distributed computation (Dask, Ray, Spark)Low-latency vs high-throughput compute tradeoffsExperience with financial or regulatory systems where correctness > speedDatabase performance tuning (Postgres, Oracle)Building internal observability for compute enginesWhat Success Looks LikeComputation engine handles large datasets reliably and predictablyCalculations are:ExplainableReproducibleAuditablePerformance scales linearly (or better) with data sizeNew rules can be added without code rewritesEdge cases are covered by testsnot discovered in productionEngineering Culture Fit

Thanks & Regards

Aishwarya J

7337692370

aishwarya.j@idexcel.com