Lead Data Engineer
The Value Maximizer, Columbia, SC, United States
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.
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
#J-18808-Ljbffr
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.
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
#J-18808-Ljbffr