Data Analytics Lead Engineer

Citi; Irving (TX); Hybrid; USD 126,000 - 189,000; Full time

Benefits offered by this job

Hybrid office schedule

Medical, dental & vision insurance

401(k) plan

Job summary

Citi is seeking a Data Analytics Lead Engineer to design, build, and operate scalable data pipelines and cloud-based data architectures for Lending analytics. This hands-on role involves big data platforms, data lakes, and AI-assisted engineering.

You will work across Mortgage and Personal Loans, ensuring production-grade data systems power analytics at scale with reliable delivery and data quality.

Qualifications

• 6+ years of hands-on experience building and managing data pipelines, data warehouses, and data lake solutions.
• Experience with cloud data platforms to build and automate ETL and data ingestion workflows.
• Proficiency in scripting languages (Python, Scala, or Shell).
• Strong relational and non-relational data modelling knowledge.
• Experience with workflow schedulers like Airflow or Autosys.
• Knowledge of DevOps practices and version control, CI/CD, and monitoring.

Responsibilities

• Build, deploy, and manage end-to-end data pipelines for large-scale lending datasets.
• Design scalable data architectures on cloud platforms with data lakes, warehouses, and streaming environments.
• Architect data schemas to meet performance and business requirements.
• Write and optimize complex SQL queries for large datasets.
• Monitor and resolve data quality issues across pipelines.
• Apply generative AI tools to accelerate engineering tasks where appropriate.
• Collaborate with Analysts, Data Engineers, and Governance teams to translate requirements.

Skills

Data pipelines

Cloud architectures

SQL & data modeling

Python/Scala

Airflow/Autosys

DevOps practices

Data visualization

Education

Bachelor's degree

Master's degree preferred

Tools

Hadoop

Spark/Databricks

Snowflake

Hive/Impala/Iceberg

Tableau/Cognos

Job description

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

At Citi, you will work as a practicing data engineer at the center of one of the world's largest financial institutions, solving complex, real‑world data challenges across lending products that serve millions of customers globally. 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.

Location: Irving Texas United States

Employment Type: Full time

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

• Medical, dental & vision coverage
• 401(k)
• Life, accident, and disability insurance
• Wellness programs
• 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.

Anticipated Posting Close Date: Sept 09, 2026

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