Technical Architect with Python and Pyspark Experience - Chennai (12-20 Yrs) Hybrid

Luxoft India; Chennai District; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Luxoft India is seeking a Senior Technical Architect (12+ years) to lead the trade surveillance platform in Chennai. Hybrid work model with three days in office weekly, immediate to 30 days notice.

Role involves shaping multi-year architecture, migrating from Q/KDB to Python/PySpark, and delivering scalable cloud-native solutions in a regulated domain. The candidate should excel in Python, PySpark, cloud platforms, and streaming tech, with strong communication to senior stakeholders and a proven

Qualifications

• 12+ years of technology experience in Investment Banking and/or Capital Markets.
• Deep proficiency in Python and PySpark including distributed processing patterns and production-grade engineering.
• Hands-on experience with at least one major cloud platform (AWS, Azure or GCP) and modern data platforms (Databricks, Snowflake, EMR, or equivalent).
• Strong grasp of streaming and event-driven architectures (Kafka, Flink, Kinesis, or similar).
• Understanding of trade lifecycle, market microstructure, and at least one regulatory regime (MAR, Dodd-Frank, MiFID II, SEBI, FINRA rules).
• Architectural thinking balanced with engineering pragmatism and ability to communicate with senior stakeholders.

Responsibilities

• Partner with Enterprise Architects to define and evolve the trade surveillance technical roadmap and align with architecture standards.
• Own end-to-end architecture for surveillance scenario development, alert generation, case management integration, and downstream tooling.
• Define reference architectures, design patterns, and guardrails for the surveillance engineering organization.
• Lead design and implementation of surveillance scenarios and alerts across asset classes (equities, fixed income, FX, derivatives).
• Drive development of scenarios and analytics in Python/PySpark and Q/KDB transitioning to cloud-native architectures.
• Establish reusable frameworks for scenario authoring, tuning, back testing, and false-positive reduction.
• Lead migration of the platform to cloud infrastructure (AWS/Azure/GCP) including compute, storage, streaming, and orchestration.
• Architect and oversee migration of libraries and frameworks from Q/KDB to Python/PySpark on distributed compute.
• Design for scale: alert generation on billions of events per day with focus on throughput, latency, and cost.

Skills

Python

PySpark

Cloud

Distributed processing

Data architecture

Stakeholder communication

Tools

Databricks

Snowflake

EMR

Kafka

Flink

Kinesis

Job description

Pl note we are looking for Technical Architect with Python , Pyspark along with Cloud experience for Chennai location who are fine to work in hybrid mode and can join immediately or within 30 days availability.

Experience - 12-23 yrs

Work Mode : Hybrid (3 days in a week in office)

Notice period- Immediate to 30 days only (Not considering 45-90 days notice period candidates currently )

Project Description

We are looking for a Senior Architect to lead the technical direction of our Trade Surveillance platform. Partnering closely with Enterprise Architects, Compliance, and Quantitative teams, this role will shape and execute the multi-year trade surveillance technology roadmap - covering scenario and alert development, platform modernization, and migration from a Q/KDB-based stack to a scalable Python/PySpark cloud-native architecture. The ideal candidate combines deep hands-on engineering credibility with the architectural maturity to influence stakeholders across business, compliance, and technology.

Responsibilities

Partner with Enterprise Architects to define and evolve the trade surveillance technical roadmap, ensuring alignment with firm-wide architecture standards, data strategy, and regulatory expectations.

Own end-to-end architecture for surveillance scenario development, alert generation, case management integration, and downstream investigator tooling.

Define reference architectures, design patterns, and engineering guardrails for the surveillance engineering organization.

Lead the design and implementation of trade surveillance scenarios and alerts across asset classes (equities, fixed income, FX, derivatives) covering market abuse typologies such as spoofing, layering, wash trades, front-running, insider trading, and cross-product manipulation.

Drive development of scenarios and analytics in both Q/KDB (current state) and Python/PySpark (target state).

Establish reusable frameworks for scenario authoring, parameter tuning, back testing, threshold calibration, and false-positive reduction.

Lead migration of the trade surveillance platform to the new cloud infrastructure (AWS / Azure / GCP), including compute, storage, streaming, and orchestration layers.

Architect and oversee the migration of scenarios, libraries, and frameworks from Q/KDB to Python/PySpark on distributed compute (Spark, Databricks, EMR, or equivalent), ensuring functional parity, performance, and auditability.

Design for scale - alert generation across billions of order and trade events per day - with focus on throughput, latency, cost optimization, and resilience.

Data & Engineering Excellence

• Define data models and ingestion patterns for orders, executions, market data, reference data, communications, and news/social feeds.
• Champion engineering best practices: CI/CD, IaC, automated testing of surveillance logic, observability, lineage, and reproducibility of alerts (critical for regulatory defensibility).
• Collaborate with Data Engineering, DevOps, and InfoSec on secure-by-design implementations.

Requirements

• 12+ years of technology experience in Investment Banking and/or Capital Markets sector
• Deep proficiency in Python and PySpark including distributed processing patterns, performance tuning, and production-grade engineering.
• Hands-on experience with at least one major cloud platform (AWS, Azure or GCP) and modern data platforms (Databricks, Snowflake, EMR, or equivalent).
• Strong grasp of streaming and event-driven architectures (Kafka, Flink, Kinesis, or similar).
• Understanding of trade lifecycle, market microstructure, and at least one regulatory regime (MAR, Dodd-Frank, MiFID II, SEBI, FINRA rules).
• Proven ability to operate at the intersection of engineering and architecture - designing on the whiteboard and coding when needed.
• Architectural thinking balanced with engineering pragmatism.
• Strong written and verbal communication; able to translate regulatory and business intent into technical design.
• Comfortable navigating ambiguity in a high-stakes, regulator-facing environment.
• Influences without authority - credible with senior engineers, enterprise architects, and compliance leadership alike.