Mastercard
FinTech
SeniorAnalyst,BigDataAnalytics&Engineering
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Analyst, Big Data Analytics & Engineering at Mastercard. Skills: Data platforms, Data engineering, Data pipelines, Data modeling. Partner with data owners. Partner with engineering teams”
Industry & Context.
Optimize cost/benefit; Optimize architecture alignment; Identify opportunities for process improvements
What They're Looking For.
Must Have
5+ years of hands-on experience building Data platforms, Proven experience as a hands-on data engineer, Deep understanding and experience with Cloudera Data Platform (CDP), Hands-on experience with PySpark, Experience with Cloudera Data Platform (CDE, CDW, Ozone, Airflow, SDX), Experience with Apache Ranger, Deep understanding of distributed data systems, Deep understanding of Hive Metastore, Experience and understanding of cataloging, Experience and understanding of lineage, Experience and understanding of governance, Experience working with SQL, Experience working with file formats (Iceberg/Parquet), Experience working with partitioning/bucketing strategies, Experience with data lifecycle management, Experience with ingestion, Experience with ETL, Experience with pruning, Experience with modeling, Experience with governance within highly regulated environment, Understanding of SDLC, Experience in establishing processes, Experience in establishing standards, Experience in establishing governance
Nice to Have
Prior experience with financial systems, Experience optimizing their integration into broader data ecosystems, Experience and knowledge of Bit Bucket, Experience and knowledge of Rally, Experience and knowledge of Jenkins, Experience modernizing enterprise finance systems, Experience modernizing regulated environments, Knowledge of CI/CD, Knowledge of data engineering best practices, Understanding of financial data structures, Understanding of accounting processes, Understanding of reconciliation workflows, Experience / understanding Open Data Contract Standard (ODCS) and its implementation
What You'll Do.
Partner with data owners
Partner with engineering teams
Partner with platform teams
Create robust data pipelines
Implement data models
Ensure alignment between business goals and technical execution
Ensure features and solutions meet business requirements
Ensure solutions meet customer needs
Participate in sprint planning
Participate in retrospectives
Participate in agile ceremonies
Adopt best practices in data engineering
Adopt automated code reviews
Adopt continuous integration/continuous delivery (CI/CD)
Optimize cost/benefit of implementing code
Optimize architecture alignment
Ensure operational efficiency
Ensure solutions align with Mastercard’s engineering principles
Ensure solutions align with Mastercard’s data principles
Ensure solutions align with Mastercard’s technical policies
Identify opportunities for process improvements
Enhance team productivity
Stay abreast of Data Platform technology trends
Stay abreast of industry best practices
Hone and maintain talent
Participate in architectural discussions
Participate in iteration planning
Participate in feature sizing meetings
Adhere to Agile processes
Participate actively in agile ceremonies
How You'll Work.
Team & Collaboration
Cross-functional teams; Business/product owners; Technical experts; Data owners; Engineering teams; Platform teams; Agile ceremonies
Process & Methodology
Agile, Sprint planning, Retrospectives, Iteration planning, Feature sizing
Full Job Description
**Our Purpose** _Mastercard powers economies and empowers people in 200 + countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential._ **Title and Summary** ### Senior Analyst, Big Data Analytics & Engineering ### Background Mastercard is on a journey to modernize and advance our Finance Technology landscape, covering Billing, Financial Planning, Accounting, Settlement, Treasury, Reporting and Analytics. This position will be responsible for developing and delivering high-impact technology solutions that align with our business and technical objectives. By collaborating with cross-functional teams, including business/product owners and other technical experts, you will ensure that our solutions meet evolving customer needs while improving performance, scalability, and reliability. Responsibilities \- Partnering with data owners, engineering and platform teams to create robust data pipelines, create Data Products, implement data models. \- Ensure alignment between business goals and technical execution, making sure features and solutions meet business requirements and customer needs. \- Participate in sprint planning, retrospectives, and other agile ceremonies to ensure the team is aligned and delivering efficiently. \- Adoption of best practices in data engineering, automated code reviews, testing, and continuous integration/continuous delivery (CI/CD). \- Optimize the cost/benefit of implementing code a certain way, architecture alignment, ensuring scalability, performance, and operational efficiency. \- Ensuring solutions align with Mastercard’s engineering and data principles, and technical
Applying for this Senior Analyst, Big Data Analytics & Engineering role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about Mastercard?
Real rants from real employees. Read before you apply.