
Data Engineer - WM
QodeSouth Carolina, SC
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Job Description
Data Engineer - Wealth Management
About the Role
We are seeking a highly skilled Data Engineer to design, build, and optimize data pipelines and solutions on AWS. The ideal candidate will have strong expertise in Python, PySpark, AWS Glue, Lambda, and Redshift, with hands-on experience in building scalable and reliable data workflows that power analytics and business decisions.
Key Responsibilities
Design, develop, and maintain ETL/ELT pipelines using AWS Glue, PySpark, and Python.
Implement serverless data workflows using AWS Lambda for automation and event-driven processing.
Build and manage data models, tables, and schemas in Amazon Redshift, ensuring performance and scalability.
Optimize data pipelines for reliability, performance, and cost-effectiveness.
Collaborate with data scientists, analysts, and business teams to deliver clean, structured, and usable datasets.
Ensure compliance with data security, governance, and best practices within AWS cloud infrastructure.
Monitor, troubleshoot, and improve existing data solutions and workflows.
Required Skills & Qualifications
Strong programming skills in Python and PySpark.
Hands-on experience with AWS services including Glue, Lambda, Redshift, S3, and CloudWatch.
Experience building ETL pipelines and transforming large-scale structured and unstructured data.
Strong understanding of data warehousing concepts and performance tuning in Amazon Redshift.
Proficiency in SQL for complex data queries and transformations.
Familiarity with version control (Git) and CI/CD for data pipeline deployments.
Problem-solving skills with the ability to work in fast-paced environments.
Preferred Qualifications
Experience with orchestration tools (e.g., Airflow, Step Functions) is a plus.
Knowledge of data governance, cataloging, and lineage tools within AWS.
Exposure to streaming frameworks (Kafka, Kinesis) is desirable.
Prior experience in agile development environments.
Education & Experience
Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field.
3+ years of professional experience as a Data Engineer or in a similar role.
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Submit 10x as many applications with less effort than one manual application.
