Data Analytics Lead Engineer

Description

Technology group, Data Analytics job family. The company's Lending business is hiring a Data Analytics Lead Engineer to work across Mortgage and Personal Loans.

You will be a hands-on data engineer building and running production data systems on big data platforms, data lakes and cloud infrastructure. Your work supports lending analytics at scale.

The company is a large financial institution whose lending products serve millions of customers worldwide. You will also understand AI and ML integration as an additional capability, on top of a strong data engineering base.

Responsibilities

• Build, deploy and run end-to-end pipelines that ingest, transform and deliver large lending datasets for Mortgage and Personal Loans, reliably and quickly.
• Design scalable cloud data architectures, choosing tools for data lakes, data warehouses and streaming.
• Design and implement schemas in relational, dimensional, normalized or partitioned form, based on performance, scale and business needs.
• Write and tune complex SQL on very large datasets, and speed up pipelines with sound choices about distributed and parallel processing.
• Monitor pipelines, find the cause of operational and data quality problems, and fix them so data stays accurate, complete and on time.
• Use generative AI tools where they help, such as for code generation, query tuning and data summaries.
• Help shape data engineering standards and work with business analysts, data engineers and data governance teams to turn business needs into sound technical solutions.

Requirements

• At least 6 years of hands-on experience building and running pipelines, warehouses and data lakes with Hadoop, Apache Spark, PySpark, Databricks, Delta Lake, Hive, Impala or Iceberg.
• Practical work on cloud data platforms such as Snowflake and Cloudera, building and automating ETL and ingestion workflows.
• Working fluency in Python, Scala or Shell scripting, used daily for data engineering, pipelines and automation.
• Ability to design and query relational and non-relational stores, weigh schema trade-offs and apply data modelling principles.
• Hands-on use of workflow schedulers such as Autosys or Apache Airflow to orchestrate pipeline runs.
• Solid DevOps habits, including version control, build tools, unit testing, monitoring and change management, for reliable, repeatable delivery.
• Experience with visualization tools such as Tableau or Cognos to present data and support reporting.
• Hold a bachelor's degree or a university qualification of equivalent level. A master's degree is preferred.
• Beneficial: exposure to cloud AI and ML services such as Amazon SageMaker, Azure Machine Learning or Google AI Platform, used to put predictive models into pipelines.
• Beneficial: familiarity with NoSQL databases such as HBase, MongoDB, Couchbase, Cassandra or Neo4j.
• Beneficial: Databricks certification, or a cloud certification in AWS, Azure or GCP.
• Beneficial: a proactive approach to troubleshooting, with the ability to find root causes alone and resolve pipeline or data issues thoroughly and quickly.

Conditions

Full-time position.

Hybrid working: 3 days in the office and 2 days remote.

Based in Irving, Texas, United States.

Salary range for the primary location: $125,760.00 - $188,640.00.

Eligible employees may also receive discretionary and formulaic incentive and retention awards. Offerings vary by jurisdiction, job level and date of hire.

The posting is expected to close on Oct 20, 2026.

Automated tools, including AI, may match your skills to roles, but people make and check every hiring decision. Illinois residents have an AI notice and right, and the company's EEO policy statement and Know Your Rights poster are available.

Benefits

• Support for continued learning and technical growth, including backing for cloud and platform certifications related to the job.
• Access to large, complex data environments and modern cloud infrastructure, where your engineering choices have a direct effect on the business.
• A collaborative team of data engineers, analysts and business partners that values and recognises hands-on technical work.
• Competitive pay and a full benefits package aimed at supporting your financial and personal wellbeing.
• Medical, dental and vision coverage, a 401(k), life, accident and disability insurance, and wellness programs.
• Paid vacation, paid sick leave and paid holidays.