Pune · Senior
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The Applications Development Intermediate Programmer Analyst is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to contribute to applications systems analysis and programming activities.
Responsibilities:
Qualifications:
Experience Level: 5 to 9 years as discussed
Key Skills:
Good to have skills:
Education:
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
We are seeking an experienced and forward-thinking Senior Big Data Engineer (7+ Years) to join our technology team. In this role, you will be responsible for designing, developing, and optimizing high-performance, large-scale data processing pipelines and regulatory data platforms using Apache Spark, Java/Scala, Spring Boot, and Python/PySpark.
The ideal candidate brings deep expertise in distributed data computing, complex Spark SQL query optimization, data analysis, and modern CI/CD DevOps workflows. You will actively leverage GenAI engineering tools (such as GitHub Copilot and Devin AI) to accelerate delivery, drive code quality, and translate complex business requirements into robust High-Level (HLD) and Low-Level Designs (LLD).
Key Responsibilities
Architect & Develop Data Solutions: Design, implement, and maintain scalable, high-throughput batch and stream data pipelines using Apache Spark, Java/Scala, and PySpark.
End-to-End System Design: Analyze business and regulatory requirements to create comprehensive High-Level Designs (HLD), Low-Level Designs (LLD), data flow diagrams, and interface specifications.
Data Engineering & Analytics: Perform in-depth data analysis across the data lifecycle—including data sourcing, schema evolution, transformation logic, quality validation, and actionable insight generation.
Spark SQL Optimization: Write, tune, and maintain complex Spark SQL queries, partitioned datasets, and transformations for optimal performance over large enterprise datasets.
Microservices & API Integration: Build enterprise-grade services and data ingestion microservices using Spring and Spring Boot.
DevOps & CI/CD Delivery: Implement automated build, test, and deployment workflows using Git/GitHub, Jenkins / Lightspeed, and Harness.
AI-Augmented Engineering: Leverage modern GenAI developer tooling (e.g., GitHub Copilot, Devin AI) to accelerate prototyping, code review, unit testing, and documentation.
Cross-Functional Collaboration: Partner closely with Product Owners, Data Analysts, Business Teams, and Quality Assurance to ensure end-to-end alignment and timely delivery.
Candidate Qualifications & Skill Set
1. Core Technical Skills (Must-Have)
Experience:5-9 years of hands-on software and data engineering experience in enterprise environments.
Distributed Computing & Big Data: Deep practical expertise in Apache Spark architecture (RDDs, DataFrames, Datasets, execution plans, memory management, partitioning, and performance tuning).
Primary Programming Languages: Advanced proficiency in Java and/or Scala, with strong object-oriented and functional programming paradigms.
Frameworks: Extensive hands-on experience building scalable applications using Java and Apache Spark.
Scripting & Python/PySpark: Strong proficiency in Python with practical experience writing data transformations using PySpark.
Data Querying & SQL: Expert-level proficiency in SQL / Spark SQL, window functions, complex joins, indexing, and query plan execution analysis (EXPLAIN).
Data Analysis & Processing: Proven ability to source, cleanse, enrich, reconcile, and validate large datasets to deliver high-integrity reporting and analytical outputs.
2. Architecture & DevOps
Solution Architecture: Proven track record of drafting clear, maintainable HLD and LLD documents, technical specifications, and data modeling artifacts.
Version Control & CI/CD: Hands-on experience with GitHub / Bitbucket, build automation with Jenkins / Lightspeed, and modern continuous delivery platforms like Harness.
3. AI Tools & Modern Engineering Practices
AI-Assisted Development: Experience utilizing AI productivity tools such as GitHub Copilot or Devin AI for test generation, code refactoring, and rapid prototyping.
Engineering Excellence: Strong commitment to test-driven development (TDD), automated unit/integration testing, SonarQube quality gates, and secure coding standards.
4. Preferred / Good-to-Have
Business Intelligence & Visualization: Experience with Tableau or similar BI visualization tools for dashboarding and reporting validation.
Domain Knowledge: Prior exposure to Banking, Financial Services, Liquidity Reporting, Regulatory Data (e.g., NDTL/LCR), or Risk Management.
5. Soft Skills & Professional Attributes
Exceptional Communication: Outstanding verbal and written communication skills; adept at explaining technical concepts to both technical peers and non-technical business stakeholders.
Ownership & Problem Solving: Proactive attitude, strong analytical reasoning, and the ability to drive initiatives from inception to production deployment.
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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
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