Sr. Data Engineer / Analyst

Overview

Sr. Data Engineer / Analyst

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.

• Partnering with data owners, engineering and platform teams to establish robust data pipelines, implement data models, and ensure seamless integration across diverse systems and domains.
• 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 software / data engineering, including automated code reviews, testing, and continuous integration/continuous delivery (CI/CD).
• Optimize the cost/benefit of software features and architecture, ensuring scalability, performance, and operational efficiency.
• Ensuring solutions align with Mastercard’s engineering and data principles, and technical policies.
• Identify opportunities for process improvements, helping to streamline workflows and enhance team productivity.
• Work closely with Product Owners / business to understand requirements and implement technical solutions with engineering best practices.
• Stay abreast of Data Platform technology trends and industry best practices to hone and maintain your talent
• Participate in architectural discussions, iteration planning, and feature sizing meetings
• Adhere to Agile processes and participate actively in agile ceremonies
  
  
  

• 8+ years of hands-on experience developing solutions on Cloud data platform, including Databricks. Proven experience as a data engineer, with a strong focus on delivering large-scale projects in an agile environment.
• Hands-on experience in Databricks and deep understanding of its architecture. Design, develop and implement large-scale, high-volume, high-performance, highly available, scalable data-based solution and pipelines for the Databricks Lakehouse platform in AWS cloud
• Hands-on experience developing and supporting data lakes, lakehouses, warehouse on-premise and on cloud, ETL solutions and other analytics solutions.
• Prior experience with financial systems, such as Oracle Financials, Oracle Fusion Cloud, and Hyperion, with experience optimizing their integration into broader data ecosystems, is a plus.
• Experience with data lifecycle management, including ingestion, ETL, pruning, modeling, and governance, within highly regulated environments.
• Expertise in modern data engineering best practices, CI/CD, automated testing, and code reviews, etc.
• Experience in partnering with data owners and other engineering and platform teams to build and manage a single source of truth for data, leveraging end-to-end technology stacks and best practices in data architecture.
• Strong programming skills in Python and frameworks, with a focus on building scalable, reliable, and performant solutions. Experience with performance engineering, ensuring systems are built to scale and meet varying demands.
• Knowledge of security best practices and experience in ensuring the secure development of applications.
• Experience in driving technical decision-making and trade-offs, balancing competing priorities such as business goals, technical constraints, and user experience.
• Ability to identify process inefficiencies and drive continuous improvement initiatives within the team.
• Experience working with development / engineering teams in a global environment.
• Experience on native AWS cloud services.
• Experience and knowledge of Bit Bucket, Rally, and Jenkins a plus
• Strong understanding of cloud DevOps practices and implementation.
• Experience in cloud data migration for large sized enterprise data warehouse environments.
• Understanding of cloud data governance, compute optimization, cost control, etc.
• Understanding cloud security models, encryption strategy, network layers for on-prem + cloud hybrid model and other related concepts.
• Understanding of any one database technology - like Exadata / Oracle / Netezza / SQL server
• Understanding of SDLC and experience in establishing processes, standards and governance to bring efficiency within development team
  
  
  

All Activities Involving Access To Mastercard Assets, Information, And Networks Comes With An Inherent Risk To The Organization And, Therefore, It Is Expected That Every Person Working For, Or On Behalf Of, Mastercard Is Responsible For Information Security And Must:

• Abide by Mastercard’s security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.