Data Engineering Manager, Vice President

Citi is looking for a Data Engineering Manager (Data Analytics Senior Manager - C13) to lead the design and delivery of scalable, high-quality data solutions that power regulatory reporting, business decision-making, and analytical capabilities across the bank. This is a hands-on technical leadership role where you will serve as a subject matter authority, shape engineering standards, and mentor a team of data engineers in a fast-paced, agile environment. If you bring deep data engineering expertise combined with the communication skills to align stakeholders and translate complex technical concepts into business outcomes, this role offers meaningful scope and impact.

Design and build scalable, highly available data pipelines and analytical data models that meet both functional requirements and the bank's long-term architectural strategy. Architect data lake solutions, batch and streaming pipelines, and distributed data systems that support regulatory, in-business, and analytics use cases. Identify risks within the data supply chain and take proactive steps to resolve or escalate them before they affect downstream consumers. Champion engineering standards, best practices, and technical documentation, raising the quality bar for the broader data engineering team. Translate complex technical concepts into clear, business-relevant language, acting as the connection point between engineering teams and business stakeholders. Mentor and coach junior and mid-level engineers, accelerating their development and embedding a culture of continuous learning and technical excellence. Lead technical discussions, support hiring decisions, and contribute to team capability-building as both an informal and formal team leader. Required Qualifications & Skills 6 or more years of experience delivering data-intensive solutions in agile environments, with a demonstrated ability to manage complexity and ambiguity at scale. Hands-on expertise building production-grade ETL pipelines using Apache Spark, with practical experience across large-scale platforms such as Hadoop, Hive, Databricks, or Snowflake. Solid grounding in data warehousing concepts, file and table formats (Parquet, Avro, and Iceberg), and data catalog technologies. Experience designing, optimizing, and maintaining analytical data models. Proficiency in SQL and Python for data engineering delivery, paired with strong familiarity with CI/CD practices, Autosys, and shell scripting. Practical knowledge of data management and governance disciplines. Strong communication and problem-solving skills, with a track record of bridging technical and non-technical stakeholders and driving data-informed decisions. A bachelor's degree or equivalent experience Beneficial Skills & Qualifications Familiarity with mortgage data domain concepts and the data structures that support mortgage business processes. Working knowledge of containerization technologies, including Docker and Kubernetes, for deploying and managing data workloads. Foundational understanding of access and entitlement management controls within data platforms. Awareness of the Generative AI landscape as it applies to data engineering, including experience with prompt engineering or AI-assisted tooling such as code generation, data summarization, or anomaly detection. A master's degree is an advantage.

Joining Citi means working at a global scale on data problems that have real consequences for one of the world's leading financial institutions. You will work within a team that values technical craft, collaborative delivery, and continuous improvement, with the tools, autonomy, and support to grow as both an engineer and a leader. A hybrid working model offering 3 days in the office and 2 days working remotely each week. Meaningful technical leadership scope, with the opportunity to shape engineering culture, standards, and practices across the team. Access to continuous learning and development resources,