Job description

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. Responsibilities • 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. What We Offer 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, supporting both formal training and on-the-job growth. • Mentorship and professional development pathways that support long-term career progression within a global organization. • Competitive compensation and financial well-being benefits commensurate with a senior technical leadership role. • Well-being and family support programs designed to help you maintain a healthy work-life balance. • Exposure to complex, large-scale data challenges across regulatory, analytical, and strategic business domains. Build the data foundations that matter. Apply now to bring your engineering expertise to a team solving real-world challenges at Citi. Note : Applicants must be authorized to work in the U.S for this position; Citi will not sponsor applicants for U.S. work authorization for this role. Candidate must be located within commuting distance or be willing to relocate to the area. 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: Data Analytics ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Primary Location: Irving Texas United States ------------------------------------------------------ Primary Location Full Time Salary Range: $125,760.00 - $188,640.00 In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire. ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Anticipated Posting Close Date: Oct 01, 2026 ------------------------------------------------------ Automated Processing and AI We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi. Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details. Illinois residents – AI Notice and Right ------------------------------------------------------ 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.

Requirements

Must-haves

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.
Technology ------------------------------------------------------
Data Analytics ------------------------------------------------------

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

agilesqlpythonci/cddockerkubernetesaiaccessibility

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Wellness

Professional Development