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Data Analytics Lead Engineer

Job in Irving, Dallas County, Texas, 75084, USA
Listing for: JobCubby
Full Time position
Listed on 2026-09-05
Job specializations:
  • IT/Tech
    Data Engineering, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 126000 - 189000 USD Yearly USD 126000.00 189000.00 YEAR
Job Description & How to Apply Below

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  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 Dev Ops 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 Sage Maker, Azure Machine Learning, or Google AI Platform, used to integrate predictive models within data pipelines.
  • Familiarity with No

    SQL 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…
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