Big Data Engineers

Hello,

Please find the below requirement and let me know your thoughts

Position:  Big Data Engineers
Location:  Charlotte, NC-Hybrid
Duration: Long Term

There is an apex tech screen and then an interview with the team if no previous Wells Fargo/good reference, previous Wells Fargo experience is highly desired - if someone has previous Wells Fargo with a good reference, will hire them without a team interview if they pass tech screen!

Two Positions:

Mid-Level and Senior Level

• Top Must-Haves:
• Deep big data engineering expertise — strong PySpark, Scala, SQL, and hands‑on experience with large‑scale data sourcing and conformance.
• Ability to build and support batch data pipelines — including Autosys, Unix shell, GitHub/CI/CD, and comfort with enterprise‑scale performance patterns.
• End‑to‑end ownership — developers must own what they build, including L3 support post–go‑live.
• Experience with complex data modernization (e.g., parsing/mapping large structured/unstructured datasets like Newton wires).

Big Data Engineer – Financial Crimes & AI Enablement

Overview

Wells Fargo 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 AI‑driven use cases that require strong, reliable data foundations.

The work centers on large‑scale data ingestion, conformance, and modernization of legacy systems—including the Newton wires platform—onto the enterprise big data environment.

Key Responsibilities

• Lead end‑to‑end development of batch‑oriented data pipelines, including raw data sourcing, domain‑level conformance, and support for downstream curation teams.
• Design, build, and optimize large‑scale 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 high‑volume structured and semi‑structured data (CLOB, JSON, SWIFT formats).
• Apply enterprise‑scale performance engineering patterns (partitioning, sorting, join optimization) to ensure reliability and throughput across petabyte‑scale 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 go‑live 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 hands‑on expertise with PySpark, Scala, Spark, and SQL.
• Proven experience with data sourcing, ingestion, and conformance on distributed data platforms.
• Demonstrated ability to own deliverables end‑to‑end, 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 AI‑related 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.

Submission details
Full Legal Name as per SSN:
Email ID:
Contact Number:
Current location (City name, State, ZIP code) :
DOB: (dd/mm)
Are you willing to relocate? (Yes/NO)
Best time to reach (Mon-Fri):
LinkedIn ID(Must) :
Initial entry of US (Visa status) and the current status Approval (year):
Are you done with your current project? (Yes/No):
(If YES please mention Last date of the Project):
Last 4 digits of SSN :
Highest Degree:
Name of the University, specialization, Location (Start Date (MM/ YYYY)– Ending Date(MM/YYYY)):
 
Professional references in below format is mandatory for client submission:
Note: GMAIL, YAHOO, OUTLOOK mails are not Considered
Reference 1 :
Client Name:
Reference Name:
Reference Job Title:
Reference Professional/ Official E-mail Address:
Reference Phone Number:
 
Reference 2 :
Client Name:
Reference Name:
Reference Job Title:
Reference Professional/ Official E-mail Address :
Reference Phone Number:
 

Thanks & Regards,
 
Vasu
Intellisoft Technologies Inc.,
11494 Luna Road, Ste 280
Farmers Branch, TX -75234
(O) ext 131