AVP Data Engineer – Banking, Hybrid, Python + Spark

Wissen Technology; Alpharetta (GA); Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Health insurance

Remote work stipend

Immigration support

Paid time off

Job summary

Wissen Technology is seeking a Senior Data Engineer (AVP/VP level) to join our expanding team in the USA with a hybrid work model. The role requires 8–12 years of enterprise data engineering experience and a strong background in Python, SQL, Spark, and cloud data pipelines within financial services.

Responsibilities include designing scalable data pipelines, building Python data components, and ensuring data governance and regulatory compliance.

Qualifications

• 8–12 years of Data Engineering experience in enterprise environments.

Responsibilities

• Design, build, and maintain scalable data pipelines for ingestion, transformation, and processing of structured and unstructured data.
• Develop Python applications and data engineering components for automation, ETL, and analytics workflows.
• Architect and optimize data models, schemas, and database structures for performance and compliance.
• Work with distributed data technologies such as Spark, Kafka, Hadoop, Databricks.
• Implement data quality frameworks, validation rules, and monitoring dashboards.
• Collaborate with business, analytics, and engineering teams to translate banking requirements into technical solutions.
• Ensure governance, security, and regulatory standards compliance (SOX, PCI, Basel, AML/KYC).
• Troubleshoot production issues and drive remediation.
• Build CI/CD pipelines and contribute to DevOps for data deployments.
• Document data flows and architecture diagrams.

Skills

Python

SQL

Spark

Airflow

Cloud platforms

CI/CD

Docker/Kubernetes

NoSQL

Education

Bachelor's or higher in CS/Engineering

Tools

Databricks

Hadoop

Kafka

Job description

Wissen Technology is seeking a Senior Data Engineer (AVP/VP level) to join our expanding team in the USA with a hybrid work model. The role requires 8–12 years of enterprise data engineering experience and a strong background in Python, SQL, Spark, and cloud data pipelines within financial services.

Responsibilities include designing scalable data pipelines, building Python data components, and ensuring data governance and regulatory compliance.