Big Data Engineer

Job Description:
Big Data Engineer - Financial Crimes & AI Enablement

Its Hybrid 3 times a week in Charlotte but I can take relos

One and Done Interviews I have times on Friday

2 year contract only on w2

Must haves:
Pyspark

Scala

SQL
Batach Data Pipeines

Overview

• Client is expanding its AI and data modernization initiatives and is seeking experienced Big Data Engineers to support critical data sourcing platform engineering and modernization efforts within the Financial Crimes organization. These roles are funded to accelerate delivery of new AIdriven use cases that require strong reliable data foundations.
• The work centers on largescale data ingestion conformance and modernization of legacy systemsincluding the Newton wires platformonto the enterprise big data environment.

Key Responsibilities

• Lead endtoend development of batchoriented data pipelines including raw data sourcing domainlevel conformance and support for downstream curation teams.
• Design build and optimize largescale data processing solutions using PySpark Scala Spark and advanced SQL.
• Support modernization initiatives such as the Newton wires rebuild including complex parsing mapping and transformation of highvolume structured and semistructured data (CLOB JSON SWIFT formats).
• Apply enterprisescale performance engineering patterns (partitioning sorting join optimization) to ensure reliability and throughput across petabytescale datasets.
• Collaborate with platform engineering financial crimes teams and AI integration groups to ensure data readiness for advanced analytics and AI use cases.
• Provide L3 production support for developed pipelines particularly during golive and stabilization phases.
• Work within established tooling and frameworks including Autosys Unix shell scripting GitHub/CI/CD JIRA/Agile FlowMaster (ingestion wrapper) and Dremio (SQL interface).

Required Qualifications

• 5 years of experience in Big Data engineering within large enterprise environments.
• Strong handson expertise with PySpark Scala Spark and SQL.
• Proven experience with data sourcing ingestion and conformance on distributed data platforms.
• Demonstrated ability to own deliverables endtoend including production support.
• Experience building and supporting batch pipelines and working with enterprise schedulers (Autosys).
• Proficiency with Unix shell scripting GitHub CI/CD pipelines and Agile development practices.

Preferred Qualifications

• Experience with financial crimes risk or transaction monitoring data domains.
• Familiarity with modernization of legacy systems (e.g. mainframe to big data migrations).
• Exposure to AIrelated data preparation or integration (AI experience is a plus not a requirement).
• Knowledge of Power BI for reporting support (beneficial for select roles).
• Prior Wells Fargo experience or returning boomerang candidates with strong references.

Required Skills:

PysparkScalaSQLBatch data pipelines