Senior Data Engineer

Job Title:

Senior Data Engineer

Overview:

Overview

Mastercard Data Warehouse builds and supports various analytics and reporting platform that includes Domo, Power BI, Tableau, SSRS and WebFOCUS. The ecosystem also includes Microsoft BI stack involving SSAS & SSIS and Alteryx ETL tool. We are looking for data engineer who can build efficient data pipelines to feed downstream reporting and analytics platform

Ideal candidates will answer yes to all of the following questions:

• Have you worked in an agile development team?

• Are you proficient in Big Data, ETL/ELT tool (example NiFi)

• Are you passionate about building technology to deliver quality solutions providing superior customer experience?

• Do you thrive in a fast-paced environment and have the ability to learn new skills and applications quickly?

Role description:
The Data Engineer II will participate on data management aspects of client engagements to deliver data products, as well as contribute to and foster a high-performance collaborative workplace. A Data Engineer II will:

- Independently execute projects through design, implementation, automation, and maintenance of large-scale enterprise ETL processes for a global client base
- Develop repeatable and scalable code that processes client data in an automated and efficient manner to ensure data availability in the platform is as real-time as possible.
- Act as an expert data resource within the team
- Manage the process of data delivery on teams by overseeing other Data Engineers and Analysts to deliver on-time, accurate, high-value, robust data solutions across multiple clients, solutions, and industry sectors
- Build trust-based working relationships with peers and clients across local and global teams
- Leverage industry best practices including proper use of source control, code reviews, data validation and testing
- Enhance big data pipelines using Python, R, SSIS and Powershell to address complex technical challenges and seamless communication with several cloud storage technologies
- Leverage new SQL Server features such as Columnstore Indexes, In-Memory OLTP, Incremental statistics, Trace Flags, SQL CLR functions, window aggregate functions, and parallel computing algorithms to reduce the processing time of multi-billion row data sets
- Contribute to the automation capabilities of the team. Implement techniques to optimize and routinize repeatable tasks
- Comply with and uphold all Mastercard internal policies and external regulations

All About You:
1. Bachelor's degree in Computer Science, Software Engineering, or a related field
2. Extensive hands-on experience in Data Engineering, including implementing multiple end-to-end data warehouse projects in Big Data environments.
3. Proficiency in application development frameworks (Python, Java/Scala) and data processing/storage frameworks (Hadoop, Spark, Kafka).
4. Experience in developing data orchestration workflows using tools such as Apache NiFi, Apache Airflow, or similar platforms to automate and streamline data pipelines.
5. Experience with performance tuning of database schemas, databases, SQL, ETL jobs, and related scripts.
6. Experience of working in Agile teams
7. Experience in development of data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale using Java, Scala, or Python. This includes all phases such as data ingestion, feature engineering, modeling, tuning, evaluating, monitoring, and presenting analytics.
8. Experience in developing integrated cloud applications with services like Azure, Databricks, AWS or GCP.
9. Excellent analytical and problem-solving skills, with the ability to analyze complex data issues and develop practical solutions.
10. Strong communication and interpersonal skills, with the ability to collaborate effectively with and facilitate activities across cross-functional teams, geographically distributed, and stakeholders. #AI3To find US Salary Ranges, visit People Place. Under the Compensation tab, select "Salary Structures." Within the text of "Salary Structures," click on the link "salary structures 2025," through which you will be able to access the salary ranges for each Mastercard job family. For more information regarding US benefits, visit People Place and review the Benefits tab and the Time Off & Leave tab.

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