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Senior Data Engineer-4

Hyderabad, Andhra Pradesh, India

Live, first seen by us 44 days ago
Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Own design and delivery of batch and real-time data pipelines on Databricks, Spark and Python

  • Build dbt transformation architecture using test-driven development and modular design

  • Design and own CI/CD pipelines in GitLab and Jenkins

  • Administer and optimize Databricks objects, managing performance, access and cost

  • Mentor junior and mid-level engineers and lead code and design reviews

From the employer’s posting
Own the end-to-end design, development, and delivery of complex batch and real-time data pipelines using Databricks, Spark, Python, and PySpark.
Drive dbt-based transformation architecture with rigorous Test-Driven Development (TDD) and modular design.
Design and own CI/CD pipelines using GitLab and Jenkins, and champion DataOps practices across the team.
Administer and optimize Databricks objects and the platform using Databricks Asset Bundles, managing performance, access, and cost.
Mentor junior and mid-level engineers, and lead code and design reviews.
Education & alternatives
Plan and execute deployments, migrations, and upgrades with minimal disruption to operations. Required Qualifications Bachelor's degree in computer science or a related technical field (Master's a plus). 5+ years of data engineering experience.
Apply at Mastercard

Posting record

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Status in our records
Live
First seen by us
Sep 30, 202644 days ago
Recorded sightings
115
Last seen by us
Nov 14, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 44

Similar jobs usually come down between day 6 and day 56.

At Mastercard, jobs usually come down by about day 25.

From 13,718 similar postings that came down, and 268 of Mastercard’s. Coming down is not always a hire.

Mastercard is hiring

72 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is steady
  • Takes jobs down quickly
  • 8% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • dbt
  • GCP
  • Kafka
  • Spark
  • PySpark
Where the posting names them
You will bring cutting edge software and full stack development skills with advanced knowledge of cloud and data lake experience while working with massive data volumes. Our teams are small, agile, and focused on the needs of the high growth fintech marketplace, and you will work across functional teams within Mastercard to deliver on our cloud strategy while keeping our systems resilient, responsive, and maintainable on cloud. Key Responsibilities Own the end-to-end design, development, and delivery of complex batch and real-time data pipelines using Databricks, Spark, Python, and PySpark. Drive dbt-based transformation architecture with rigorous Test-Driven Development (TDD) and modular design.
5+ years of data engineering experience. Deep hands-on experience with Databricks (including administration), Spark, and Python. Strong background in PySpark and distributed data processing.
Experience with real-time data processing and streaming pipelines. Expert SQL development and strong cloud infrastructure experience (AWS, Azure, or GCP). Demonstrated experience mentoring engineers and leading technical delivery.
Design and own CI/CD pipelines using GitLab and Jenkins, and champion DataOps practices across the team. Administer and optimize Databricks objects and the platform using Databricks Asset Bundles, managing performance, access, and cost. Establish data observability frameworks covering quality, freshness, lineage, and anomaly detection.
Proven track record using dbt for robust, testable transformation workflows following TDD. Familiarity with Databricks Asset Bundles for object deployment and version control. Strong CI/CD (GitLab, Jenkins) and DataOps expertise.
Key Responsibilities Own the end-to-end design, development, and delivery of complex batch and real-time data pipelines using Databricks, Spark, Python, and PySpark. Drive dbt-based transformation architecture with rigorous Test-Driven Development (TDD) and modular design. Design and own CI/CD pipelines using GitLab and Jenkins, and champion DataOps practices across the team.
Strong background in PySpark and distributed data processing. Proven track record using dbt for robust, testable transformation workflows following TDD. Familiarity with Databricks Asset Bundles for object deployment and version control.
Establish data observability frameworks covering quality, freshness, lineage, and anomaly detection. Lead the design of real-time data streaming pipelines (e.g., using Kafka, Spark Structured Streaming). Mentor junior and mid-level engineers, and lead code and design reviews.
Deep hands-on experience with Databricks (including administration), Spark, and Python. Strong background in PySpark and distributed data processing. Proven track record using dbt for robust, testable transformation workflows following TDD.

Your next step

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About Mastercard

People
About 39,800 in 2025, up 13% from the year before.Annual report (SEC Form 10-K)
Company
Listed as MA.
H-1B visas
36 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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 Data Engineer-4

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
Mastercard is seeking a Senior Data Engineer to join our team in Hyderabad, India. This is an experienced individual-contributor role that owns end-to-end pipeline delivery and mentors peers. It will appeal to you if you combine deep technical expertise with the ability to independently deliver complex data solutions and raise the bar for the engineers around you.

You will bring cutting edge software and full stack development skills with advanced knowledge of cloud and data lake experience while working with massive data volumes. Our teams are small, agile, and focused on the needs of the high growth fintech marketplace, and you will work across functional teams within Mastercard to deliver on our cloud strategy while keeping our systems resilient, responsive, and maintainable on cloud.

Key Responsibilities
Own the end-to-end design, development, and delivery of complex batch and real-time data pipelines using Databricks, Spark, Python, and PySpark.

Drive dbt-based transformation architecture with rigorous Test-Driven Development (TDD) and modular design.

Design and own CI/CD pipelines using GitLab and Jenkins, and champion DataOps practices across the team.

Administer and optimize Databricks objects and the platform using Databricks Asset Bundles, managing performance, access, and cost.

Establish data observability frameworks covering quality, freshness, lineage, and anomaly detection.

Lead the design of real-time data streaming pipelines (e.g., using Kafka, Spark Structured Streaming).

Mentor junior and mid-level engineers, and lead code and design reviews.

Partner with stakeholders on requirements, delivery planning, and technical trade-offs.

Plan and execute deployments, migrations, and upgrades with minimal disruption to operations.

Required Qualifications
Bachelor's degree in computer science or a related technical field (Master's a plus).

5+ years of data engineering experience.

Deep hands-on experience with Databricks (including administration), Spark, and Python.

Strong background in PySpark and distributed data processing.

Proven track record using dbt for robust, testable transformation workflows following TDD.

Familiarity with Databricks Asset Bundles for object deployment and version control.

Strong CI/CD (GitLab, Jenkins) and DataOps expertise.

Experience with real-time data processing and streaming pipelines.

Expert SQL development and strong cloud infrastructure experience (AWS, Azure, or GCP).

Demonstrated experience mentoring engineers and leading technical delivery.

Ideally you have experience in banking, e-commerce, credit cards or payment processing and exposure to both SaaS and premises-based architectures. In addition, you have a post-secondary degree in computer science, mathematics, or quantitative science.

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.




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Hyderabad, Andhra Pradesh, India

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