Data Engineer-2

Mastercard

3.6

(14)

Pune, India

Why you should apply for a job to Mastercard:

  • 4.8/5 in supportive management
  • 71% say women are treated fairly and equally to men
  • 100% say the CEO supports gender diversity
  • Ratings are based on anonymous reviews by Fairygodboss members.

    #22331_R-246504

    Position summary

    igger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities.

    Our team within Mastercard - Services:

    The Services org is a key differentiator for Mastercard, providing the cutting-edge services that are used by some of the world's largest organizations to make multi-million dollar decisions and grow their businesses. Focused on thinking big and scaling fast around the globe, this agile team is responsible for end-to-end solutions for a diverse global customer base. Centered on data-driven technologies and innovation, these services include payments-focused consulting, loyalty and marketing programs, business Test & Learn experimentation, and data-driven information and risk management services.

    Data Analytics and AI Solutions (DAAI) Program:

    Within the D&S Technology Team, the DAAI program is a relatively new program that is comprised of a rich set of products that provide accurate perspectives on Portfolio Optimization, and Ad Insights. Currently, we are enhancing our customer experience with new user interfaces, moving to API and web application-based data publishing to allow for seamless integration in other Mastercard products and externally, utilizing new data sets and algorithms to further analytic capabilities, and generating scalable big data processes.

    We are looking for an innovative software engineering lead who will lead the technical design and development of an Analytic Foundation. The Analytic Foundation is a suite of individually commercialized analytical capabilities (think prediction as a service, matching as a service or forecasting as a service) that also includes a comprehensive data platform. These services will be offered through a series of APIs that deliver data and insights from various points along a central data store. This individual will partner closely with other areas of the business to build and enhance solutions that drive value for our customers.

    Engineers work in small, flexible teams. Every team member contributes to designing, building, and testing features. The range of work you will encounter varies from building intuitive, responsive UIs to designing backend data models, architecting data flows, and beyond. There are no rigid organizational structures, and each team uses processes that work best for its members and projects.

    Here are a few examples of products in our space:

    Portfolio Optimizer (PO) is a solution that leverages Mastercard's data assets and analytics to allow issuers to identify and increase revenue opportunities within their credit and debit portfolios.
    Ad Insights uses anonymized and aggregated transaction insights to offer targeting segments that have high likelihood to make purchases within a category to allow for more effective campaign planning and activation.
    Help found a new, fast-growing engineering team!

    Position Responsibilities:

    As a Data Engineer within DAAI, you will:

    Play a large role in the implementation of complex features
    Push the boundaries of analytics and powerful, scalable applications
    Build and maintain analytics and data models to enable performant and scalable products
    Ensure a high-quality code base by writing and reviewing performant, well-tested code
    Mentor junior engineers and teammates
    Drive innovative improvements to team development processes
    Partner with Product Managers and Customer Experience Designers to develop a deep understanding of users and use cases and apply that knowledge to scoping and building new modules and features
    Collaborate across teams with exceptional peers who are passionate about what they do

    Ideal Candidate Qualifications:

    4+ years of data engineering experience in an agile production environment
    Experience leading the design and implementation of large, complex features in full-stack applications
    Ability to easily move between business, data management, and technical teams; ability to quickly intuit the business use case and identify technical solutions to enable it
    Experience leveraging open source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform analyses
    • High proficiency in using Python or Scala, Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi, Scoop), SQL to build Big Data products & platforms
    • Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale in Java, Scala, or Python and deliver analytics involving all phases like data ingestion, feature engineering, modeling, tuning, evaluating, monitoring, and presenting
    Experience in cloud technologies like Databricks/AWS/Azure
    Strong technologist with proven track record of learning new technologies and frameworks
    Customer-centric development approach
    Passion for analytical / quantitative problem solving
    Experience identifying and implementing technical improvements to development processes
    Collaboration skills with experience working with people across roles and geographies
    Motivation, creativity, self-direction, and desire to thrive on small project teams
    Superior academic record with a degree in Computer Science or related technical field
    Strong written and verbal English communication skills

    Corporate Security Responsibility

    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.

    Why you should apply for a job to Mastercard:

  • 4.8/5 in supportive management
  • 71% say women are treated fairly and equally to men
  • 100% say the CEO supports gender diversity
  • Ratings are based on anonymous reviews by Fairygodboss members.