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Team Overview

The team is focused on building and evolving job manager and distributed processing solutions using Apache Spark and cloud technologies. This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.

Role Overview And Core Responsibilities

Architecture & Solution Design

Responsibilities

Design scalable and resilient data processing solutions using Apache Spark and contemporary data platform technologies. Create architecture designs, reference patterns, and technical specifications for distributed data platforms. Guide engineering teams on architecture, design, and implementation decisions. Ensure solutions align with enterprise architecture standards, security requirements, and engineering best practices. Evaluate technology choices, frameworks, and platform capabilities to address evolving business needs. Identify architectural risks and recommend mitigation strategies.



Contribute to platform modernization and cloud transformation initiatives.

Apache Spark & Data Platform Leadership

Responsibilities

Provide technical leadership for Apache Spark-based batch and streaming data processing solutions. Guide development teams on Spark architecture, performance optimization, and operational best practices. Define design patterns for scalable, fault-tolerant, and maintainable Spark applications. Assist teams in resolving complex technical challenges involving distributed processing and large-scale data workloads. Drive performance improvements through effective partitioning, query optimization, resource management, caching, and tuning strategies. Establish standards for observability, monitoring, reliability, and operational excellence.

Solution Architecture & Engineering Guidance

Responsibilities

Collaborate with engineering teams throughout the software development lifecycle. Conduct architect

📌 Architect - Data Engineer (Hyderabad)
🏢 TransUnion
📍 Hyderabad