Lead Data Engineer

Senior/ Lead Data Engineer (AWS) – Wealth Management

Location: Fort Mill, NC (Hybrid)

Employment Type: Full-Time

Role Overview

We are seeking a Senior Data Lead Engineer with deep expertise in wealth management / financial services and strong hands-on skills in Python based data engineering. This role will lead the design, development, and optimization of enterprise-scale data platforms supporting portfolio management, client reporting, risk analytics, and regulatory compliance. You will act as a technical leader, driving modern data architecture, mentoring teams, and partnering with business stakeholders to deliver high-impact data solutions.

Key Responsibilities

Data Engineering & Architecture

• Design and build scalable data pipelines using Python (PySpark, Pandas, Airflow).
• Architect data lakes / warehouses (Snowflake, Redshift, or similar).
• Implement real-time and batch data processing frameworks.
• Optimize data models for analytics, reporting, and ML use cases.

Wealth Management Domain

Work with datasets across

• Portfolio & asset management
• Trade lifecycle & transaction data
• Client onboarding & KYC
• Performance reporting & attribution
• Build systems supporting investment analytics, risk, and regulatory reporting.

Leadership & Strategy

• Lead a team of data engineers; provide technical guidance and code reviews.
• Define data engineering best practices, governance, and standards.
• Collaborate with Product, Analytics, and Business teams.
• Drive data quality, lineage, and observability frameworks.

Cloud & Platform Engineering

Develop solutions on AWS

S3, Glue, Lambda, EMR, Redshift

• Implement CI/CD pipelines and infrastructure-as-code (Terraform/CloudFormation).
• Ensure security and compliance (FINRA, SEC considerations).

Required Qualifications

• 10+ years of experience in data engineering / data platform development
• 3+ years in a lead or architect role
• Strong programming expertise in Python

Hands-on experience with

PySpark / Spark

• SQL & data modeling
• Workflow orchestration (Airflow, Prefect)
• Experience in wealth management / asset management / financial services

Strong understanding of

• Investment data models
• Market data & financial instruments
• Experience with cloud-native data platforms (AWS)

Preferred Qualifications

Experience with Snowflake / Databricks

• Knowledge of machine learning pipelines
• Familiarity with data governance tools (Collibra, Alation)
• Exposure to real-time streaming (Kafka, Kinesis)

Certifications in AWS or Data Engineering

Key Skills

Python (Advanced)

Data Architecture & Modeling

Financial / Wealth Management Domain

Cloud Data Engineering (AWS)

Leadership & Stakeholder Management

ETL / ELT Pipelines

Big Data Technologies

What Success Looks Like

• Scalable, high-performance data pipelines supporting critical investment workflows
• High data quality, governance, and compliance adherence
• Strong collaboration across business and technology teams
• Mentored and high-performing data engineering team

Why Join Us

Work on mission-critical financial data platforms

High visibility with business and executive stakeholders

Opportunity to shape next-gen data architecture in wealth management

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