Data Engineer II

Mastercard is hiring a Data Engineer II in Pune, India. Level rates it ; you can apply on Mastercard.

Level's read on this job

On Level's scale, this data engineer role is Little AI ●○○○: aI is not part of the work.
Tools and skills the posting cites include Microsoft SQL Server, Alteryx and Microsoft Fabric.
Level classifies it as a mid-level role.
Level lists 1,100+ other open roles at Mastercard.
The role was posted within the past week.

AI in this role

Data engineer to build and operate scalable data pipelines and solutions supporting analytics and enterprise data platforms.

microsoft-sql-serveralteryxmicrosoft-fabric

data-engineeringetldata-pipelinesdata-warehousing

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

Data Engineer II

Who is Mastercard?

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.

Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Overview

The Insights & Enablement Data Engineering team within Services is looking for a Data Engineer II based in Pune, India, to help build, enhance, and operate scalable, reliable, and governed data solutions that support analytics and data-driven decision making.

Our Data Engineering environment spans established on-premises capabilities and an evolving cloud data platform. The team maintains and enhances the Analytics Data Mart (ADM), powered by Microsoft SQL Server and data integration workflows using Alteryx, while expanding cloud-native capabilities through the Strategy & Operations Data Platform (SODP) on Microsoft Fabric. The broader platform direction emphasizes governed production data, reusable data products, analytics, automation, and AI consumption.

You will join a collaborative Data Engineering team focused on building reusable engineering patterns, improving data quality and resiliency, automating repeatable processes, and making trusted enterprise data easier for downstream teams to consume.

Role

As a Data Engineer II, you will:

-Develop, test, enhance, and maintain data pipelines and data solutions that ingest, transform, and deliver enterprise data for analytics and downstream consumption using Alteryx and Fabric pipelines.
-Work independently on defined elements of Data Engineering projects, applying established engineering standards and patterns while collaborating with experienced engineers on more complex designs.
-Develop and support solutions across our data ecosystem, including Microsoft SQL Server, Alteryx, and the growing Microsoft Fabric platform, while contributing to the team's transition toward scalable cloud-native data engineering patterns.
-Monitor and troubleshoot identifiable data pipeline and processing issues by analyzing logs, identifying root causes, and applying appropriate solutions to maintain data availability and reliability.
-Apply Data Engineering practices for data quality, security, validation, documentation, and operational resiliency, helping ensure solutions are trustworthy and supportable in production.
-Collaborate with Data Engineering colleagues, business stakeholders, and partner teams to understand requirements, review deliverables, assess technical feasibility, and translate data needs into maintainable technical solutions.
-Document technical designs, data processes, reusable patterns, and operational procedures while contributing to continuous improvement and knowledge sharing across the team.

All About You

The ideal candidate for this position should:

-Have intermediate/practical Data Engineering expertise, with the ability to independently develop, test, troubleshoot, and maintain data pipelines and related components using established engineering practices.
-Be proficient with SQL and relational data concepts, including data transformation, data modeling, database design, and building reliable solutions for analytical use cases.
-Have practical experience with modern data integration and workflow orchestration concepts, including moving and transforming data across multiple enterprise data sources and platforms.
-Understand core practices related to data quality, data security, testing, monitoring, troubleshooting, and operational reliability, and apply them throughout the Data Engineering lifecycle.
-Be comfortable working with technologies such as Microsoft SQL Server, Python and cloud-based data platforms; experience with Microsoft Fabric, Lakehouse architectures, Data Factory/Data Pipelines, OneLake, or Alteryx would be valuable for this team.
-Be an effective collaborator and communicator who can document technical solutions clearly, contribute to solution reviews and planning discussions, learn new technologies, and work effectively with both technical and business stakeholders.

Corporate Security Responsibility
Every person working for, or on behalf of, Mastercard is responsible for information security. All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and therefore, it is expected that the successful candidate for this position 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.

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.

How we rate this

Data Engineer II at Mastercard rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Engineer II is an open job at Mastercard.
Level rates this role AI Level 1 of 4: Little AI.
The role is based in Pune, India.
The job was posted on October 19, 2026.
Seniority: mid.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data EngineeringETLData PipelinesData WarehousingMicrosoft SQL ServerAlteryxMicrosoft Fabric

Also common in data engineer jobs at this level

AWS Spark Azure Airflow Databricks Google Cloud

Pay

Typical data engineer job: $150k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data pipelines was part of your work. What did you do?
Tell me about a project where data warehousing was part of your work. What did you do?
Walk me through how you've used Microsoft SQL Server in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Data Engineering, ETL, Data Pipelines, Data Warehousing, and Microsoft SQL Server. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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