Senior Data Engineer Lead - Senior Vice President

Position: Senior Data Engineer Lead  - Senior Vice President
At Citi Services - Global Trade Technology Organization, we are on a mission to harness the power of data to drive innovation, create exceptional customer experiences, and solve complex business challenges. Our data team is at the heart of this mission, building the scalable and resilient infrastructure that turns data into our most valuable asset. We are a passionate, collaborative group dedicated to pushing the boundaries of what's possible.

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* The Opportunity:

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* Are you a seasoned data expert who loves to build as much as you love to lead? Do you believe that a great data culture is the foundation for a great data platform? We are looking for a Senior Data Engineering Lead to be a player-coach for our talented data engineering team.

This is a unique, high-impact role for someone who is both a visionary architect and a hands-on builder. You will not only design our next-generation data architecture but also roll up your sleeves and write the code that brings it to life. More importantly, you will be the primary champion for a world-class data engineering culture, setting the standard for technical excellence, innovation, and collaboration.

You will lead by example, mentoring engineers, and establishing practices that empower the entire organization to build with data confidently.

** What You'll Do:*
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** Architect & Design:
** Design, architect, and oversee the development of robust, scalable, and reliable data infrastructure, including data lakes, data warehouses, and real-time streaming platforms on the cloud.

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** Build & Code:
** Act as a senior individual contributor and hands-on technical leader. Write clean, maintainable, and high-performance code for data ingestion, transformation, and serving layers (e.g., using Python, Scala, SQL, and Spark).

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** Lead & Mentor:
** Lead a team of data engineers, providing technical guidance, mentorship, and career development support. Foster a collaborative and inclusive team environment.

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** Champion Culture:
** Define, document, and champion data engineering best practices across the organization, including CI/CD, data quality, testing frameworks, observability, and code review standards.

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** Drive Strategy:
** Partner with leadership, product managers, data scientists, and analysts to understand data needs and develop a long-term data strategy and roadmap.

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** Innovate & Evaluate:
** Stay at the forefront of data engineering technologies. Evaluate, prototype, and recommend new tools and frameworks to continuously improve our data platform.

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** Ensure Governance:
** Implement and enforce robust data governance, security, and privacy policies in partnership with our security and compliance teams.

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* Qualifications:

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* + 10+ years of professional experience in data engineering, with a proven track record of designing and building large-scale data systems.

+ 3+ years in a technical leadership or architect role, with experience mentoring junior and senior engineers.

+ Expert-level proficiency in at least one programming language (Python or Scala preferred) and exceptional SQL skills.

+ Proven hands-on experience with Python or Scala for data manipulation, scripting, machine learning, and backend development.

+ Deep, hands-on experience with a major cloud platform (AWS, GCP, or Azure) and its data ecosystem (e.g., S3/GCS, Redshift/Big Query, EMR/Dataproc, Kinesis/Dataflow).

+ Extensive hands-on experience with modern big data technologies and Data streaming (like Hadoop, Hive, Impala, Apache Spark, Kafka, or Flink)

+ Proficiency with workflow orchestration tools such as Airflow, Dagster, or Prefect.

+ Proficiency in designing and implementing microservices architectures, RESTful APIs, and event-driven systems with 'Data as a Product' Principle.

+ Solid understanding of data modeling concepts and database design for both analytical (OLAP) and transactional (OLTP) workloads.

+ Deep understanding and hands-on experience with relational databases (e.g., Postgre

SQL, Oracle), No

SQL databases (e.g., Mongo

DB, Cassandra), data warehousing, and big data technologies (e.g., Spark, Kafka).

+ Experience building and maintaining CI/CD pipelines for data applications (e.g.,…