Hadoop Developer

Define target state architecture and strategic roadmap for surveillance data processing platforms leveraging Hadoop,Spark, Pyspark and Python

Establish standard architectural patterns for alert generation, enrichment, aggregation and reporting pipelines.

Ensure architecture aligns with enterprise technology standards and Surveillance control expectation

Solution Design and Delivery Support

Translate surveillance business requirements(e.g, market misconduct detection, regulatory coverage) into scalable technical designs

Review and approve detailed technical designs, ensuring alignment with functional intent, regulatory requirements, and architectural standards.

Provide hands-on architectural guidance to engineering teams during development, testing and implementation

Design and standardization of Spark/Pyspark frameworks supporting surveillance alert generation and enrichment

Modernization and Optimization of large-scale Hadoop surveillance workloads to improve performance, stability and control coverage

Implementation of enterprise-consistent architecture patterns enabling audit readiness, lineage, and regulatory traceability

Support end-to-end delivery across the SDLC, minimizing rework and technical debt

Architecture Governance & Leadership

Participate in and lead architecture review forums and design walkthroughs

Mentor senior engineers and promote adoption of Standard framework and best practices

Influence enterprise surveillance platform strategy through architecture governance

Documentation & Communication

Maintain high-quality documentation, including business requirement, data definitions and process flows

Proactively communicate risks, dependencies and potential timeline impact to stakeholders

Primary Skill: Data Engineering, Platform Engineering or architecture roles. Deep Expertise in Pyspark.

Experience: 10+ yrs

Roles & Responsibilities

Bachelor s or master s degree in computer science or related field.

Required Hard and Soft Skills / Experience

Deep Expertise in PySpark, including performance tuning and optimization

Strong python development experience in large-scale distributed environment

Solid knowledge of Hadoop ecosystem (HDFS,Hive/Impala, YARN)

Proven experience designing and governing enterprise, regulatory facing data platforms.

Expertise in designing data lakes, ELT/ETL pipelines, batch and real time data processing solution

Proficiency in programming languages such as Java, Scala and SQL

Strong understanding of non-functional requirements and production support models

Clear written and verbal communication skills with ability to influence across organizations

Preferred Skills / Experience

Financial services experience, particularly in Market Surveillance, AML, Fraud, Or Risk Technology

Experience supporting regulatory or audit facing platforms

Kafka and Spark Structured streaming exposure

Familiarity with Orchestration tools(Airflow,Control-M,Oozie)

Knowledge of data governance, lineage, and data quality controls