Senior Data Engineer II

Title: Senior Data Engineer II
No H1B or CPT
Location: Arlington, VA(Locals, Onsite, Inperson)
Duration: 12+ months possibility for extension!!!
Contract :: W2

Experience :: 13+ years only

Note :: Inperson Needed

Glider: Data Engineering – Advanced

For IT roles only, is Java required?  
Spark
Hadoop
Python


Job Description Summary
Role:
• Support the design, implementation, and maintenance of enterprise ETL processes for data platforms, for a global client base.
• Develop scalable and efficient code to process data, ensuring availability and accessibility in a timely manner.
• Leverage big data processing frameworks such as Apache Spark and Hadoop to build and optimize data pipelines.
• Collaborate with senior engineers to address data challenges, contributing to solutions that maintain high data quality.
• Assist in the data delivery process, working alongside Data Engineers and Analysts to support accurate, high-value data solutions across various clients and industries.
• Build strong working relationships with team members and clients, contributing to both local and global projects.
• Learn and apply industry best practices, including version control, code reviews, and data validation, to ensure quality in data processes.
• Use SQL and other database technologies to help optimize data processing and reduce the time required to handle large data sets.
• Design, implement, and maintain data pipelines using ETL frameworks, orchestration tools, and distributed data processing engines.
• Participate in efforts to automate routine data tasks and streamline processes.
• Comply with all Mastercard internal policies and adhere to external regulations.

All About You:
• Experience as a Data Engineer or in a similar role, with a strong understanding of data engineering concepts and methodologies.
• Strong knowledge of writing and optimizing SQL queries to retrieve, manipulate, and analyze data efficiently.
• Hands-on experience with big data technologies such as:
o Apache Spark (PySpark, Spark SQL, Spark Streaming)
o Hadoop ecosystem (HDFS/ Ozone, Hive, YARN)
• Familiarity with ETL frameworks and the ability to design, implement, and maintain data pipelines.
• Understanding data modeling concepts and database design to support scalable data solutions.
• Familiarity with Python.
• Ability to analyze and troubleshoot data issues and provide solutions with minimal supervision.
• Basic knowledge of testing and validating data to ensure accuracy and consistency in data pipelines.
• Excellent verbal and written communication skills, with the ability to articulate complex ideas clearly and concisely to both technical and non-technical stakeholders.
• Bachelor''''''''''''''''s degree in quantitative discipline such as Engineering, Mathematics, Finance, Business, or a related field. Equivalent practical experience may also be considered.