Job Summary

Senior Architect role in a multinational organization focused on building scalable data and analytics solutions using Python LakeHouse platforms Spark Job Definition OneLake SQL and PySpark. The role requires deep expertise in retail banking data and processes delivering secure and performant hybrid cloud data architectures that drive business value in a hybrid work model with day shift.

Responsibilities

- Design robust LakeHouse based data architectures that integrate OneLake Spark Job Definition and PySpark components to support large scale retail banking analytics and reporting use cases
- Develop end to end data pipelines using Python SQL and PySpark that efficiently ingest transform and curate transactional and customer data from multiple retail banking source systems
- Optimize Spark Job Definition configurations and job orchestration to achieve predictable performance cost efficiency and high reliability for critical banking workloads
- Implement secure data models and access patterns in LakeHouse and OneLake environments that align with retail banking regulatory requirements and internal risk policies
- Collaborate with product owners and domain experts in retail banking to translate business goals into technical data architecture blueprints and implementation roadmaps
- Guide engineering teams on best practices for coding standards performance tuning and reusable patterns in Python SQL and PySpark across hybrid environments
- Review solution designs technical specifications and implementation plans to ensure alignment with enterprise architecture standards and long term data strategy
- Coordinate with cloud infrastructure and security teams to ensure LakeHouse and OneLake solutions meet resilience observability and compliance expectations
- Create detailed documentation for data models data flows pipeline configurations and operational runbooks to support sustainable day to day operations by delivery teams




- Mentor less experienced team members by providing constructive feedback technical coaching and examples of effective patterns for data engineering in banking contexts
- Engage with stakeholders to evaluate new data platform features and tools assessing their suitability for retail banking use cases and recommending adoption paths
- Drive continuous improvement initiatives by analyzing production issues identifying root causes and implementing architectural enhancements that reduce risk and improve stability
- Align data solution outcomes with organizational goals by demonstrating how improved data quality timeliness and accessibility enable better customer experiences in retail banking

Qualifications

- Require extensive experience designing and implementing LakeHouse based data platforms with OneLake or comparable technologies in complex enterprise environments
- Require strong hands on expertise in Python SQL and PySpark for building scalable data pipelines reusable libraries and automation frameworks supporting analytics and reporting
- Require deep domain knowledge of retail banking including deposits loans cards customer journeys and regulatory reporting to ensure solutions meet functional expectations
- Require proven experience working with Spark Job Definition including job configuration resource tuning monitoring and optimization for both batch and near real time workloads
- Require experience in hybrid work environments collaborating across global teams using structured documentation version control and standard agile practices
- Nice to have experience designing solutions that integrate LakeHouse platforms with downstream analytics tools dashboards and machine learning workflows in banking scenarios
- Nice to have exposure to data governance practices such as data cataloging lineage tracking and quality frameworks that enhance trust in banking data products
- Nice to have familiarity with performance engineering techniques on large relational datasets using advanced SQL optimization and partitioning strategies

Certifications Required Preferred certifications include Microsoft Azure Data Engineer Associate or Databricks Data Engineer Skilled or equivalent data engineering certifications

📌 Sr. Architect (Chennai)
🏢 Cognizant
📍 Chennai