Senior Data Engineering Lead - Vice President

LocationPune Maharashtra India

Work modehybrid

Typefull-time

SeniorityVP

Experience10–15 yrs

DepartmentTechnology

Company size10,000+ people

First seenOct 8, 2026 · 3d ago

Verified live1d ago

At a glanceSummarised by Seekless from the posting.

Bachelor's/University degree or equivalent experience in computer science, engineering, or similar domain

10-15 years of hands-on experience in Hadoop, Scala, Java, Spark, Hive, Kafka, Impala, Unix Scripting and other Big data frameworks

4+ years of experience with relational SQL and NoSQL databases: Oracle, MongoDB, HBase

Strong proficiency in Python and Spark Java with knowledge of core spark concepts and Scala and SQL

Data Integration, Migration & Large Scale ETL experience (Common ETL platforms such as PySpark/DataStage/AbInitio etc.)

Data Modeling experience (OLAP, OLTP, Logical/Physical Modeling, Normalization, knowledge on performance tuning)

Experienced in working with large and multiple datasets and data warehouses

Experience building and optimizing 'big data' data pipelines, architectures, and datasets

Strong analytic skills and experience working with unstructured datasets

Ability to effectively use complex analytical, interpretive, and problem-solving techniques

Experience with Confluent Kafka, Redhat JBPM, CI/CD build pipelines and toolchain – Git, BitBucket, Jira

Experience with external cloud platform such as OpenShift, AWS & GCP

Experience with container technologies (Docker, Pivotal Cloud Foundry) and supporting frameworks (Kubernetes, OpenShift, Mesos)

Experienced in integrating search solution with middleware & distributed messaging - Kafka

Highly effective interpersonal and communication skills with tech/non-tech stakeholders

Experienced in software development life cycle and good problem-solving skills

Excellent problem-solving skills and strong mathematical and analytical mindset

Ability to work in a fast-paced financial environment

Skills

Hadoop

Scala

Java

Spark

Hive

Kafka

Impala

Unix Scripting

SQL

NoSQL

Oracle

MongoDB

HBase

Python

Spark Java

PySpark

DataStage

AbInitio

Confluent Kafka

Redhat JBPM

Git

BitBucket

Jira

OpenShift

AWS

GCP

Docker

Pivotal Cloud Foundry

Kubernetes

Mesos

About the role

The Applications Development Technology Lead Analyst is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead applications systems analysis and programming activities.

Responsibilities:

Data Engineering Lead a strategic professional who stays abreast of developments within own field and contributes to directional strategy by considering their application in own job and the business.

Recognized technical authority for an area within the business. Requires basic commercial awareness. There are typically multiple people within the business that provide the same level of subject matter expertise. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Significant impact on the area through complex deliverables. Provides advice and counsel related to the technology or operations of the business. Work impacts an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.

Responsibilities:

• Strategic Leadership: Define and execute the data engineering roadmap for Global Wealth Data, aligning with overall business objectives and technology strategy. This includes understanding the data needs of portfolio managers, investment advisors, and other stakeholders in the wealth management ecosystem.

• Team Management: Lead, mentor, and develop a high-performing, globally distributed team of data engineers, fostering a culture of collaboration, innovation, and continuous improvement.

• Architecture and Design: Oversee the design and implementation of robust and scalable data pipelines, data warehouses, and data lakes, ensuring data quality, integrity, and availability for global wealth data. This includes designing solutions for handling large volumes of structured and unstructured data from various sources.

• Technology Selection and Implementation: Evaluate and select appropriate technologies and tools for data engineering, staying abreast of industry best practices and emerging trends specific to wealth management data.

• Performance Optimization: Continuously monitor and optimize data pipelines and infrastructure for performance, scalability, and cost-effectiveness, ensuring optimal access to global wealth data.

• Collaboration: Partner with business stakeholders, data scientists, portfolio managers, and other technology teams to understand data needs and deliver effective solutions that support investment strategies and client reporting.

• Data Governance: Implement and enforce data governance policies and procedures to ensure data quality, security, and compliance with relevant regulations, particularly around sensitive financial data.

Recommended Qualifications:

•10-15 years of hands-on experience in Hadoop, Scala, Java, Spark, Hive, Kafka, Impala, Unix Scripting and other Big data frameworks.

• 4+ years of experience with relational SQL and NoSQL databases: Oracle, MongoDB, HBase

• Strong proficiency in Python and Spark Java with knowledge of core spark concepts (RDDs, Dataframes, Spark Streaming, etc) and Scala and SQL

• Data Integration, Migration & Large Scale ETL experience (Common ETL platforms such as PySpark/DataStage/AbInitio etc.) - ETL design & build, handling, reconciliation and normalization• Data Modeling experience (OLAP, OLTP, Logical/Physical Modeling, Normalization, knowledge on performance tuning)

• Experienced in working with large and multiple datasets and data warehouses

• Experience building and optimizing ‘big data’ data pipelines, architectures, and datasets.

• Strong analytic skills and experience working with unstructured datasets

• Ability to effectively use complex analytical, interpretive, and problem-solving techniques• Experience with Confluent Kafka, Redhat JBPM, CI/CD build pipelines and toolchain – Git, BitBucket, Jira

• Experience with external cloud platform such as OpenShift, AWS & GCP

• Experience with container technologies (Docker, Pivotal Cloud Foundry) and supporting frameworks (Kubernetes, OpenShift, Mesos)

• Experienced in integrating search solution with middleware & distributed messaging - Kafka

• Highly effective interpersonal and communication skills with tech/non-tech stakeholders.

• Experienced in software development life cycle and good problem-solving skills.

• Excellent problem-solving skills and strong mathematical and analytical mindset

• Ability to work in a fast-paced financial environment

Education

•

Bachelor’s/University degree or equivalent experience in computer science, engineering, or similar domain.

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

Job Family Group:

Technology

Job Family:

Applications Development

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.

Legal

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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