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Must Have Technical/Functional Skills
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.
Must Have Technical/Functional Skills
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
- Daily Responsibilities/Priorities
- Enterprise & Surveillance Architecture
- 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
- Non-Functional requirement and product Readiness