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Job Description & How to Apply Below
Senior Software Engineer – Market Data
Team: Beacon Risk & Pricing Platform Level: Senior
Location:
Mumbai, Noida
About Beacon Platform By CWAN
Beacon is a cloud-native, cross-asset risk analytics and quantitative development platform used by top-tier asset managers and banks. It provides a transparent, extensible environment for building, deploying, and scaling valuation models, pricing libraries, and risk analytics across asset classes — including derivatives, structured products and fixed income — combining pre-built financial applications with a flexible developer infrastructure that enables quants and model developers to write custom pricing and valuation logic, run scenario analysis, and integrate models directly into front-office and risk workflows, all without the constraints of legacy systems.
Role Overview
We are looking for a Senior Software Engineer to join the Market Data Team supporting the Beacon Risk & Pricing Platform — the industry's leading real-time risk analytics and pricing solution trusted by the world's largest asset managers and insurers. You will design, build, and operate the market data pipelines that power Beacon's pricing and risk engines. Working closely with quant researchers, risk modellers, and platform engineers across our nimble, globally distributed team, you will ensure market data is sourced, ingested, and stored with accuracy, completeness, and timeliness.
This is a high-ownership role where you will leverage cutting-edge, Python-based cloud-native technologies to make architectural decisions that directly shape how Clearwater consumes, normalizes, and stores market data at scale, with real consequences for the pricing models and portfolios we serve.
What You'll Do
Market Data Pipelines
Design and build scalable Python-based ETL/ELT pipelines ingesting multi-asset market data (equities, fixed income, derivatives, FX, commodities) from multiple market data vendors
Build, Enhance and Support data feeds using home ground data ingestion frameworks in Python.
Architect cloud-native, multi-tenant data infrastructure on AWS (S3, Mongo
DB, Elasti Cache).
Implement data quality frameworks — completeness checks, anomaly detection, stale-data alerting, and automated reconciliation against authoritative vendor sources.
Collaboration & Leadership
Partner with quantitative analysts and risk engineers to translate data requirements into reliable, production-grade pipelines.
Define and document data contracts, SLAs, and lineage so downstream pricing and risk models can trust the data they consume.
Collaborate with global teams, conduct code reviews, and champion engineering best practices across the teams.
Engage directly with external data vendors on API integrations, licensing, entitlement management, and data quality escalations.
Respond to client queries on market data, troubleshooting and resolving data issues in a timely manner, escalating to vendors where necessary.
Required
What You'll Bring
7+ years of hands-on software engineering experience, with at least 4 years building production data pipelines in Python (Pandas, PySpark, asyncio, or equivalent).
Deep hands-on experience with AWS data services: S3, Glue, Lambda, Kinesis / MSK, Redshift, RDS.
Experience designing and implementing REST APIs for data distribution, including versioning, authentication, and rate-limiting for high-throughput financial data consumers.
Strong understanding of market data domains — pricing, corporate actions, identifier mapping, instrument reference data — from a financial services or fintech context.
Proficiency in SQL and data modelling for analytical and operational workloads.
Familiarity with data quality patterns: schema validation, reconciliation, SLA monitoring, dead-letter queues, and alerting.
Strong communication skills — you write clear design docs, run productive tech discussions, and collaborate across disciplines and ability to work in a global team environment.
Degree (B.Tech / M.Tech / MCA) in computer science or an engineering field.
Preferred
Prior integration with major market data vendors (Bloomberg, Refinitiv/LSEG Elektron, ICE Data Services).
Knowledge of Apache Airflow or similar workflow orchestration tools.
Experience with Apache Iceberg, Delta Lake, or other open table formats for data lake management.
AWS Professional or Specialty certifications (Data Analytics, Solutions Architect).
Skills At a Glance
Highly Experienced in Python
Market Data Pipelines
Reference Data & Securities Master
AWS (S3, Lambda, Glue, EMR, Elasti Cache) MongoDB
Cloud-Native Data Architecture
Streaming & Event-Driven Systems
Data Quality & Reconciliation
ETL/ELT Frameworks
SQL & Data Modelling.
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