Data Engineering Manager, Vice President

We need to output HTML fragment with sections: About the role (maybe intro), Responsibilities, Requirements (or Qualifications), Skills (maybe combine), Benefits, Pay, Schedule. Must only include sections that have real content. Must not repeat job title as heading. Must not include Job ID etc. Must remove boilerplate. We need to parse the posting. Intro: "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." That's prose for About the role. Responsibilities: list bullet points after "Responsibilities". The text: "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." We need to split into list items. Each sentence separated by period? Actually they are concatenated without spaces after periods. We'll split by period and treat each as bullet. Qualifications: "Required Qualifications & Skills" then list bullet points. Let's extract: - 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 Then "Beneficial Skills & Qualifications" list: - 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. We could combine Required Qualifications & Skills and Beneficial Skills into a single "Requirements" section? The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We can have both Qualifications and Skills separate if content exists. But we have both required qualifications and beneficial skills. Could put Required Qualifications under "Qualifications" and Beneficial Skills under "Skills". Or combine. The instruction: Prefer a few substantive sections over many thin ones. So maybe combine qualifications and skills into one "Requirements" section, but we have both required and beneficial. Could still have "Requirements" with sublist? But we must use

• for any list. Could have two lists under same heading? Probably okay to have one heading "Requirements" and include both required and beneficial as separate lists with headings? But we cannot add extra headings beyond those specified? Not prohibited but better to keep simple. Could have "Qualifications" for required, and "Skills" for beneficial. That's two sections. Now Benefits: The posting includes "What We Offer" with bullet points: - 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. But we must not include filler like "commensurate with experience" etc. The phrase "Competitive compensation and financial well-being benefits commensurate with a senior technical leadership role." includes "commensurate with a senior technical leadership role." That's somewhat vague but still specific? It's not a placeholder like "commensurate with experience". It's okay. However we also have Pay section separate: they gave salary range: "$125,760.00 - $188,640.00". Also mention discretionary and formulaic incentive and retention awards, benefits etc. So we should create Pay section with that salary range. Benefits section can include other benefits: hybrid working model, learning resources, mentorship, compensation (but we already have pay), well-being programs, etc. However we must not duplicate content. We'll put salary range in Pay. Benefits: hybrid working model, technical leadership scope, learning resources, mentorship pathways, well-being and family support programs, exposure to complex data challenges, building data foundations. Also maybe mention "Joining Citi means working at a global scale..." that's more about role; could be in About the role? Already we have intro. Could keep as part of Benefits? But it's more about the company. Might be okay to keep in About the role? The intro already covers some. We'll keep Benefits as the bullet points from "What We Offer" excluding the salary range (which we put in Pay) and maybe exclude the generic "Joining Citi means working at a global scale..." as it's more about the role; but we can keep it as part of Benefits if we want. However to avoid duplication, we could keep it in About the role? The About the role already had intro; we could add that as a separate paragraph? But we must not invent. The intro didn't include that global scale line. It's in What We Offer. So we could add a paragraph under About the role? But the instruction: Prefer few substantive sections. We could add a second paragraph under About the role: "Joining Citi means working at a global scale on data problems that have real consequences for one of the world's leading financial institutions." That seems appropriate. Thus About the role will have two paragraphs: first intro, second that line. Now Benefits: list the rest. Schedule: hybrid working model offering 3 days in office, 2 days remote each week. That's schedule info. Could be under Schedule section. Pay: salary range. Now we must not include boilerplate like "Note: Applicants must be authorized to work in the U.S..." etc. Remove. Also remove "Job Family Group", "Job Family", "Time Type", "Primary Location", etc. Those are metadata; we could fold minor metadata into a short

  or drop it. The instruction: "do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it." So we could include location etc in a short p maybe under About the role? But better to drop as not essential? The location is substantive: Primary Location: Irving Texas United States. Could be included as a short p. But we have no heading for location; we could add a

  after About the role: "Location: Irving, Texas, United States." That's minor metadata. We'll include as a short p. Also "Time Type: Full time" could be included. But we must not create headings for those. Thus final HTML:

  About the role

  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.

  Joining Citi means working at a global scale on data problems that have real consequences for one of the world's leading financial institutions.

  Location: Irving, Texas, United States. Time Type: Full time.

  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.

  Qualifications

  • 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

  Skills

  • 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