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Python Developer
Python DeveloperIdexcel • Delhi, India
Python Developer

Python Developer

Idexcel • Delhi, India
1 day ago
Job description

Dear Candidate,

Greetings for the Day !!

We are Hiring for Python Developer position for our Internal Engineering Team, Please fiond below attached JOB Description,

JOB Description :

Designation : Senior Python Developer

Company Name : IDEXCEL technologies, Full Time.

Experience : (5 - 10) Years

Notice Period : immediate

Work Mode : Work From Office( 5 Days in a week)

Mode OF Interview : 1st Round Virtual (F2F), 2nd Round In-Person

Work Locations : Hyderabad

Job Description :

Senior Software Engineer – Python (Computation & Rules Engine)

Role Overview

We 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 performance—not UI and not business analysis.

Core Engineering Responsibilities

  • Design and implement pure computation modules in Python with :
  • Deterministic outputs
  • Idempotent execution
  • Strong guarantees around precision and reproducibility
  • Build a rule execution framework supporting :
  • Declarative rule definitions
  • Versioning and effective dating
  • Rule dependency graphs
  • Short-circuiting and prioritization
  • Implement high-volume data pipelines to :
  • Load, validate, normalize, and transform large datasets
  • Execute calculations efficiently in batch and incremental modes
  • Optimize performance across :
  • CPU usage
  • Memory footprint
  • IO patterns
  • Parallel execution (where appropriate)
  • Design explainability artifacts :
  • Structured calculation traces
  • Rule evaluation graphs
  • Intermediate state snapshots
  • Implement numerically safe calculations :
  • Decimal arithmetic
  • Explicit rounding strategies
  • Stable aggregation and reconciliation logic
  • Build robust testing infrastructure :
  • Unit tests for individual rules
  • Property-based tests for invariants
  • Golden dataset regression tests
  • Design APIs and internal interfaces for :
  • Batch execution
  • Streaming / delta-based recalculation
  • Downstream consumers (services, workflows)

Required Technical Skills

  • Strong proficiency in Python (5+ years preferred)
  • Deep experience with data-intensive systems, including :
  • pandas / Polars
  • NumPy
  • PyArrow
  • SQL-backed pipelines
  • Strong understanding of :
  • Algorithmic complexity
  • Memory-efficient data structures
  • Vectorized vs row-based execution tradeoffs
  • Experience building :
  • Rules engines
  • Calculation engines
  • Compilers / interpreters / evaluators
  • Solid grasp of :
  • Deterministic system design
  • Idempotency
  • Fault-tolerant batch processing
  • Strong testing discipline, including :
  • pytest
  • Property-based testing (Hypothesis)
  • Reconciliation and diff-based validation
  • Preferred / Advanced Engineering Experience

  • Designing DSLs or configuration-driven execution engines
  • Working with large datasets (10M+ rows) or wide schemas
  • Parallel and distributed computation (Dask, Ray, Spark)
  • Low-latency vs high-throughput compute tradeoffs
  • Experience with financial or regulatory systems where correctness >
  • speed

  • Database performance tuning (Postgres, Oracle)
  • Building internal observability for compute engines
  • What Success Looks Like

  • Computation engine handles large datasets reliably and predictably
  • Calculations are :
  • Explainable
  • Reproducible
  • Auditable
  • Performance scales linearly (or better) with data size
  • New rules can be added without code rewrites
  • Edge cases are covered by tests—not discovered in production
  • Engineering Culture Fit

  • You enjoy working on hard correctness problems
  • You prefer clean abstractions over quick hacks
  • You think in terms of systems and invariants
  • You care deeply about performance and observability
  • Create a job alert for this search

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