Job Title:  Assistant Manager | Full Stack Development | Bengaluru Eco space | Regulatory & Financial Risk

Job requisition ID ::  103273
Date:  Jun 3, 2026
Location:  Bengaluru Eco space
Designation:  Assistant Manager
Entity:  Deloitte Touche Tohmatsu India LLP

Assistant Manager | Full Stack Development | Bengaluru Eco space | Regulatory & Financial Risk
Job requisition ID : 103273 
Location: Bengaluru Eco space
Entity: Deloitte Touche Tohmatsu India LLP 

Assistant Manager | Regulatory, Risk & Forensic | Regulatory and Financial Risk | Full Stack Development

  • Location: Bangalore

The team

 

Deloitte Strategy, Risk & Transaction helps entities mitigate risk while discovering new opportunities to create value. Our end-to-end risk services span all domains, from managing strategic risks in the C-Suite to improving board oversight, and from balancing financial and environmental policies to addressing cyber threats. Learn more about Risk, Regulatory & Forensic)

 

Your work profile

 

  • We are looking for a skilled Senior Developer with strong expertise in PySpark to design, build, and maintain scalable data processing solutions.
  • The ideal candidate will have experience working across the data engineering stack, strong knowledge of distributed computing, and hands-on exposure to SDLC-based project development. 
  • We are seeking an experienced Python Backend Developer to design, build, and maintain scalable backend systems and APIs.
  • The ideal candidate has strong expertise in Python frameworks, database design, and backend performance optimization. 
  • We are looking for a DevOps Engineer to build, automate, and maintain scalable, secure, and highly available infrastructure.
  • The ideal candidate has strong experience in cloud platforms, CI/CD automation, and modern DevOps practices.
  • Design, develop, and optimize large-scale data pipelines using PySpark. 
  • Build and maintain ETL/ELT workflows to process structured and unstructured data. 
  • Work with big data technologies such as Hadoop ecosystem, Spark, and Impala. 
  • Collaborate with cross-functional teams including data scientists, analysts, and product teams. 
  • Ensure code quality through best practices, code reviews, and version control. 
  • Optimize job performance, memory management, and execution time in Spark jobs. 
  • Work on data modeling, transformation, and pipeline orchestration. 
  • Participate in end-to-end SDLC activities including requirement analysis, design, development, testing, and deployment. 
  • Troubleshoot and resolve data processing issues and production incidents. 
  • Contribute to automation, monitoring, and logging frameworks.

Key Responsibilities: 

  • Strong hands-on experience with Python and PySpark (mandatory). 
  • Strong SQL skills including advanced querying and performance tuning. 
  • Experience with distributed data systems such as Hadoop and Spark ecosystem. 
  • Experience with Impala, Hive, and SQL Server or other relational databases. 
  • Strong understanding of data structures, algorithms, and performance optimization. 
  • Experience with ETL pipeline development and data warehousing concepts. 
  • Knowledge of SDLC methodologies (Agile/Scrum preferred). 
  • Familiarity with version control systems such as Git. 
  • Experience working with large datasets in production environments. 
  • Knowledge of C# or other programming languages. 
  • Experience with cloud platforms such as Azure, AWS, or GCP. 
  • Exposure to workflow orchestration tools like Airflow or Oozie. 
  • Understanding of data lakes, data governance, and data quality frameworks. 
  • Experience with CI/CD pipelines. 
  • Strong analytical and problem-solving abilities. 
  • Good communication and collaboration skills. 
  • Ability to work independently and in a fast-paced environment. 
  • Proactive mindset with attention to detail. 
  • Preferred Candidate Profile: 
  • Hands-on PySpark developer with real-time project delivery experience. 
  • Exposure to end-to-end data pipeline lifecycle. 
  • Comfortable handling large-scale data processing and optimization challenges.
  • Bacheler’s degree in any specialization
  • Experience: 4–5 years in software or data engineering.