Lead Data Engineer

Qode • Columbia, SC

4h • Hybrid

About The Position

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.

Requirements

• 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)

Nice To Haves

• 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

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).

Benefits

• Work on mission-critical financial data platforms
• High visibility with business and executive stakeholders
• Opportunity to shape next-gen data architecture in wealth management

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1-10 employees