Senior Data Engineer - Apache Spark and SQL - Vice President

Citi; New York (NY); Hybrid; USD 26,000 - 48,000; Full time

Job summary

Citi is seeking a Senior Data Engineer in Pune, India, hybrid, full-time. You will modernize data pipelines on Databricks on AWS, refactor Spark jobs, and design scalable, production-ready solutions. You’ll translate architecture into concrete designs and collaborate with global teams to drive high-impact data initiatives.

The role requires 11+ years in data engineering, strong Spark/Databricks on AWS, Delta Lake, and SQL, with a focus on performance tuning and cloud-native architecture.

Qualifications

• 11+ years in data engineering or distributed systems.
• Strong expertise in Apache Spark (JavaSpark / PySpark), Databricks on AWS, and Delta Lake.
• Experience with SQL and large-scale distributed data processing.
• Experience modernizing legacy data platforms into cloud-based architectures.
• Ability to translate architecture into implementable designs.

Responsibilities

• Platform Engineering & Modernization: refactor Spark pipelines to Databricks architectures; replace Hadoop dependencies; optimize processing.
• Databricks Native Development: build and optimize solutions with Delta Lake and Databricks Workflows.
• Design & Solution Engineering: contribute to architecture, data models, and reusable components; ensure scalable, production-ready designs.
• Performance Optimization & Simplification: improve Spark performance and simplify pipelines.
• Engineering Standards & Best Practices: write clean, modular code; contribute to shared libraries.
• Collaboration & Stakeholder Engagement: work with senior architects, platform teams, and DevOps; provide guidance.
• Testing & Quality Assurance: develop unit/integration/data validation tests; support releases.

Skills

Data engineering experience

Apache Spark

Databricks on AWS

Delta Lake

SQL

AWS services

Distributed systems

Education

Bachelor’s degree

Tools

Databricks

AWS

Job description

Senior Data Engineer - Apache Spark and SQL - Vice President

Discover your future at Citi

Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview

We are looking for a highly skilled Senior Databricks Engineer to contribute to the engineering, modernization, and continuous evolution of data processing platform on Databricks on AWS. While supporting the transition from the legacy Cloudera Hadoop platform to Databricks on AWS, this role will continue to play a key part in enhancing performance, simplifying pipelines, and delivering new capabilities on the Databricks platform over the long term.

The ideal candidate is a strong hands‑on Spark engineer with solid design experience, capable of contributing to architectural decisions while leading complex implementation and optimization efforts.

Responsibilities

1. Platform Engineering & Modernization

• Refactor and modernize existing Spark pipelines to Databricks native architectures
• Eliminate legacy Hadoop dependencies and adopt cloud native AWS patterns
• Enhance and extend existing processing logic using optimized Spark (JavaSpark / PySpark) on Databricks

2. Databricks Native Development

• Build and optimize solutions using Databricks features, including Delta Lake, Databricks Workflows for orchestration and Auto scaling and job clusters

3. Design & Solution Engineering

• Contribute to low and mid level architecture and design
• Translate high level architecture into detailed technical designs
• Define data models, pipeline patterns, and reusable components
• Ensure solutions are scalable, maintainable, and production ready

4. Performance Optimization & Simplification

• Analyze, improve Spark job performance and simplify complex or over engineered pipelines into standardized, efficient patterns

5. Engineering Standards & Best Practices

• Follow and contribute to Databricks and Spark engineering standards
• Write clean, modular, and testable code
• Contribute to shared frameworks, reusable libraries, and quality standards

6. Collaboration & Stakeholder Engagement

• Work closely with senior architects, platform teams, and DevOps engineers
• Provide technical inputs, troubleshooting support, and implementation guidance
• Participate in design discussions and technical decision making

7. Testing & Quality Assurance

• Develop unit, integration, and data validation tests
• Support production releases and post deployment validation

Qualifications

Core Technical Skills

• 11+ years in data engineering or distributed systems
• Strong expertise in Apache Spark (JavaSpark / PySpark), Databricks on AWS, and Delta Lake
• Experience on SQL
• Experience with AWS services and large‑scale distributed data processing

Modernization & Optimization Experience

• Experience modernizing or refactoring legacy data platforms into cloud‑based architectures
• Strong background in Spark performance tuning and large‑scale batch optimization

Design Capability

• Ability to translate architecture into implementable designs
• Understanding of data modeling and pipeline orchestration patterns

Behavioral Competencies

• Strong problem‑solving mindset for complex distributed systems
• Comfortable working in time‑bound, high‑impact environments
• Proactive, accountable, and collaborative
• Clear communication skills across global teams

Education

• Bachelor’s degree/University degree or equivalent experience

Location(s)

Pune, Maharashtra, India

Job Type

Hybrid

Time Type

Full time

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

Job Family Group

Technology

Job Family

Applications Development

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