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Skills: Data Engineering, Python, SQL, Apache Iceberg, Apache Kafka
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$142k–$213k/yr
Full-time
bachelor degree, postgraduate degree
Medical coverage, Dental coverage, Vision coverage, 401(k), Life insurance, Accident insurance
Posted 13d ago
~40 hrs/week
Responsibilities
The Lead Data Engineer will architect and scale enterprise data platforms to support advanced analytics, machine learning, and Generative AI capabilities. They will lead a team to design high-performance data pipelines and establish technical standards for the company's data ecosystem.
Requirements
Candidates must have a bachelor's degree and at least 6 years of experience in data or software engineering, including 3 years in a leadership role. Expert-level proficiency in Python, SQL, and big data frameworks like Apache Kafka and Flink is required.
Full job description
Citi is looking for a Lead Data Engineer – AI & Distributed Analytics to architect and scale the enterprise data platforms that power our advanced analytics, machine learning, and Generative AI capabilities. In this high-impact role, you will lead a team of data engineers to design and deliver production-grade, high-performance data pipelines that bridge raw data and intelligent applications across the enterprise. You will work at the forefront of data innovation, collaborating directly with Data Scientists, AI Researchers, Product Managers, and Enterprise Architects to shape the technical direction of Citi's data ecosystem.
Responsibilities
Define and drive the technical vision, architecture, and roadmap for Citi's enterprise Data Lake and Analytics platform, ensuring alignment with cloud-native and hybrid-cloud strategies.
Lead, mentor, and develop a team of data engineers, setting technical standards and fostering a culture of continuous learning and agile delivery.
Design and build robust batch and real-time streaming data pipelines using technologies such as Apache Iceberg, Starburst, Startree/Apache Pinot, Apache Kafka, and Apache Flink to support enterprise-scale data processing.
Architect and implement Feature Stores to standardize feature engineering and ensure consistent, reliable data delivery for model training and real-time ML inference.
Optimize data storage and query performance across Enterprise Data Lakes and Lakehouses, leveraging platforms such as Delta Lake, Apache Iceberg, and Databricks.
Implement end-to-end metadata management and data lineage tracking to provide full visibility into how data flows from source systems through to AI models and analytics consumers.
Establish automated data quality frameworks — including validation rules, reconciliation checks, and compliance controls — to ensure all pipelines meet enterprise security standards and data privacy regulations such as GDPR and CCPA.
Evaluate and prototype emerging data technologies and frameworks, translating findings into actionable recommendations that keep Citi's data platform at the cutting edge.
Required qualifications & skills
Bachelor's degree, university degree, or equivalent professional experience in Computer Science, Data Engineering, Information Systems, or a quantitative field.
6 or more years of professional experience in data engineering, software engineering, or data platform development, including 3 or more years in a technical lead or engineering leadership role.
Expert-level proficiency in Python and SQL, with hands-on experience designing and delivering large-scale, distributed data systems.
Deep expertise in big data frameworks including Apache Iceberg, Startree/Apache Pinot, and Hive/HDFS, with a strong command of distributed computing principles.
Hands-on experience building and operating real-time streaming pipelines using Apache Kafka and Apache Flink at high volume and scale.
Demonstrated ability to design and build data infrastructure specifically supporting machine learning, advanced analytics, or AI applications in production environments.
Experience working with modern table formats and transactional storage layers such as Delta Lake, Apache Iceberg, or Apache Hudi.
Solid experience with workflow orchestration tools such as Apache Airflow or equivalent modern orchestrators to manage complex pipeline dependencies.
Beneficial skills & qualifications
Master's degree in Computer Science, Data Engineering, Information Systems, or a related quantitative discipline.
Additional programming proficiency in Java
Experience with cloud data platforms such as Databricks, including cluster tuning and lakehouse architecture optimization.
Familiarity with vector databases — such as Milvus, Pinecone, Qdrant, or Chroma — for GenAI and large language model use cases.
Understanding of dimensional modeling, Data Vault, and schema-on-read/write design patterns for enterprise analytics workloads.
Hands-on experience with containerization and infrastructure tooling including Docker, Kubernetes, and Terraform for Infrastructure as Code.
What we offer
At Citi, you will work at genuine scale — building data infrastructure that directly shapes how one of the world's leading financial institutions leverages AI and analytics. This is a role where your technical decisions carry real weight, your leadership develops the next generation of data engineers, and your work delivers measurable impact across the enterprise.
Hybrid working model with 3 days in the office and 2 days working remotely, giving you flexibility alongside strong team collaboration.
Opportunity to lead high-impact, enterprise-scale data engineering initiatives at the intersection of big data, machine learning, and Generative AI.
Access to continuous learning and professional development resources to keep your technical skills at the forefront of the industry.
A performance-driven environment where your contributions are recognized and directly tied to your career progression.
Competitive compensation and a comprehensive financial wellbeing package reflective of the seniority and strategic importance of the role.
Wellbeing support and work-life balance programmes designed to help you perform at your best inside and outside of work.
Collaboration with world-class Data Scientists, AI Researchers, and Enterprise Architects on problems of genuine global scale.
Build the data foundation that powers Citi's AI-driven future — apply today and take ownership of one of the most strategically important engineering platforms in global financial services.
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.
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.
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.
Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. We have over 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. We are Citi, the global bank – an institution connecting millions of people across hundreds of countries and cities.
For information on Citi’s commitment to privacy, visit on.citi/privacy.
Offices: 388 Greenwich Street, New York, New York 10013, US · Locations in over 100 countries, http://www.citigroup.com/citi/global/index.htm, 10022, US · 5900 Hurontario St, Mississauga, ON L5R 0B8, CA · 165 Jalan Ampang, Kuala Lumpur, Federal Territory of Kuala Lumpur 50450, MY · Calle 62C O, Panama City, Panama, PA
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How much do Technology jobs in Jersey City, NJ pay?
Based on 847 listings with disclosed salaries, most technology jobs in Jersey City, NJ pay between $104k–$230k per year. Individual offers vary with seniority, company size, and specialization.
How many Technology jobs are open in Jersey City, NJ right now?
There are currently 977 open technology positions in Jersey City, NJ listed on Clera. New openings are added daily as companies post roles.
Which companies are hiring for Technology roles in Jersey City, NJ?
Companies currently hiring include JPMorganChase, Bank of America, Amazon, Citi, The Depository Trust & Clearing Corporation (DTCC), among others. Browse the listings above to see every active employer.
Are there remote or hybrid Technology jobs in Jersey City, NJ?
Yes — 485 of the 977 open technology positions offer remote or hybrid work (114 remote, 371 hybrid).
How do I apply for Technology jobs in Jersey City, NJ?
Each listing links directly to the employer's application page. Apply early — fresh listings get the most recruiter attention in the first two weeks.