Data Analytics Lead Engineer

Citibank (Switzerland) AG; Irving (TX); Hybrid; Confidential; Full time

Benefits offered by this job

Hybrid work model

Job summary

Citi in Irving, Texas is seeking a Data Analytics Lead Engineer to design, build and operate scalable data pipelines and cloud-based architectures for Lending analytics across Mortgage and Personal Loans. This hands-on role runs across big data platforms, data lakes, and cloud infrastructure, with a focus on integrating AI/ML capabilities and ensuring data quality, performance, and business impact.

You will collaborate with Analysts, Data Engineers, and Governance teams while leveraging tools

Qualifications

• 6+ years building and managing data pipelines, data warehouses, and data lake solutions.
• Experience with cloud data platforms including Snowflake, Cloudera; ETL and data ingestion workflows.
• Fluency in Python, Scala, or Shell scripting.

Responsibilities

• Build, deploy, and manage end-to-end data pipelines for large lending datasets.
• Design scalable cloud data architectures across data lakes, warehouses, and streaming environments.
• Architect and implement data schemas to meet performance and scalability requirements.
• Write and optimize SQL queries for large datasets.
• Monitor, diagnose, and resolve data quality issues in pipelines.
• Apply generative AI tools to accelerate engineering tasks.
• Collaborate with analysts, data engineers and governance teams to translate requirements into solutions.

Skills

Data engineering

Cloud data platforms

SQL proficiency

Python/Scala

Workflow orchestration

DevOps practices

Data visualization

Education

Bachelor's degree or equivalent

Master's degree preferred

Tools

Hadoop

Apache Spark

PySpark

Databricks

Delta Lake

Hive

Impala

Iceberg

Snowflake

Cloudera

Tableau

Cognos

Airflow

Autosys

Job description

Data Analytics Lead Engineer

Citi is looking for a Data Analytics Lead Engineer to design, build, and operate scalable data pipelines and cloud-based data architectures within our Lending business, spanning Mortgage and Personal Loans. This is a hands‑on data engineering role where you will develop and maintain production‑grade data systems — working across big data platforms, data lakes, and cloud infrastructure — that directly power lending analytics at scale. You will also bring an understanding of AI and ML integration as an additional capability applied within a strong data engineering foundation.

Responsibilities

• Build, deploy, and manage end‑to‑end data pipelines that ingest, transform, and deliver large‑scale lending datasets across Mortgage and Personal Loans with high reliability and performance.


• Design and implement scalable data architectures on cloud platforms, selecting the right tools and approaches across data lakes, data warehouses, and streaming environments.


• Architect and implement data schemas — choosing from relational, dimensional, normalized, or partitioned models — to meet performance, scalability, and business requirements.


• Write and optimize complex SQL queries against large‑scale datasets, applying sound decisions around distributed and parallel processing to improve pipeline efficiency.


• Monitor, diagnose, and resolve operational and data quality issues across pipelines to ensure accuracy, completeness, and timely delivery of data.


• Apply generative AI tools to accelerate core engineering tasks such as code generation, query optimization, and data summarization where appropriate.


• Contribute to data engineering standards and collaborate with Business Analysts, Data Engineers, and Data Governance teams to translate business requirements into robust technical solutions.

Required Qualifications & Skills

• 6+ years of hands‑on experience building and managing data pipelines, data warehouses, and data lake solutions using technologies such as Hadoop, Apache Spark, PySpark, Databricks, Delta Lake, Hive, Impala, and Iceberg.


• Practical experience with cloud data platforms including Snowflake, Cloudera, used to build and automate ETL and data ingestion workflows.


• Fluency in one or more scripting languages — Python, Scala, or Shell Scripting — applied actively to data engineering, pipeline development, and automation tasks.


• Strong ability to design and query relational and non‑relational data stores, with a clear understanding of schema design trade‑offs and data modelling principles.


• Hands‑on experience with workflow scheduling tools such as Autosys or Apache Airflow to manage and orchestrate data pipeline execution.


• Confident use of DevOps practices including version control, build tools, unit testing, monitoring, and change management to support reliable and repeatable delivery.


• Experience with data visualization platforms such as Tableau, Cognos to support data presentation and reporting needs.


• A Bachelor's degree or equivalent university qualification; a Master's degree is preferred.

Beneficial Skills & Qualifications

• Exposure to cloud‑based AI and ML services such as Amazon SageMaker, Azure Machine Learning, or Google AI Platform, used to integrate predictive models within data pipelines.


• Familiarity with NoSQL database technologies such as HBase, MongoDB, Couchbase, Cassandra, or Neo4j.


• Databricks certification or cloud platform certification in AWS, Azure, or GCP.


• A proactive approach to troubleshooting — able to independently investigate root causes and resolve pipeline or data issues with thoroughness and pace.

What We Offer

We offer the technical scale and team environment to do meaningful engineering work, alongside the flexibility and investment to support your continued growth.

• Hybrid working model with 3 days in the office and 2 days working remotely, providing flexibility alongside team collaboration.


• Access to large‑scale, complex data environments and modern cloud infrastructure where your engineering decisions have direct business impact.


• Continuous learning and technical development support, including backing for cloud and platform certifications relevant to your work.


• A collaborative team of data engineers, analysts, and business partners where hands‑on technical contribution is valued and visible.


• Competitive compensation and a comprehensive benefits package designed to support your financial and personal wellbeing.

Build the data foundations that power real lending decisions at global scale —

Other Information

Full time

Primary Location: Irving Texas United States

Salary Range: $125,760.00 - $188,640.00

Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi 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.

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 your 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.

Anticipated Posting Close Date: Sept 09, 2026