Data Engineer

Tasks

• Designing, developing, and optimizing data pipelines for large-scale data processing, transformation, and analysis using Big Data and GCP technologies.
• Building event processing pipelines with Kafka or GCP PubSub.
• Provide engineering expertise to the team for developing features for Banking including Financial Crimes, Anti-money Laundering platforms
• Improve engineering practices, including driving resilience, predictability, and end efficiency through aut

Requirements

• 5+ years of hands-on software development experience with Big Data & Analytics solutions
• GCP Cloud - Big Query, Airflow, DataProc, PubSub, Hadoop Hive, Spark, Python, shell scripting
• Proficiency in SQL and database systems, with experience in designing and optimizing data models for performance and scalability.
• Design and development experience with Airflow, PubSub Kafka, Git, Jenkins is desirable.
• Knowledge of distributed (multi-tiered) systems, algorithms & relational databases.
• Strong Object-Oriented Programming skills and design patterns.
• Experience with CICD pipelines, Automated test frameworks, and source code management tools (XLR, Jenkins, Git).
• Good knowledge and experience with configuration management tools like GitHub
• Ability to analyze complex data engineering problems, propose effective solutions, and implement them effectively.
• Ability and willingness to learn, adopt and build solutions using the Enterprise frameworks established for Big Data
• Looks proactively beyond the obvious for continuous improvement opportunities.
• Communicates effectively with product and cross functional team.
• Willingness to learn new technologies and leverage them to their optimal potential.
• Understanding of various SDLC methodologies, familiarity with Agile & scrum ceremonies.
• Certifications in cloud platform (GCP Professional Data Engineer) is a plus.

Location

• Charlotte, NC / San Antonio, TX