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.
Hyderabad, Andhra Pradesh, India
Live, first seen by us 44 days agoOwn 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
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.
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.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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.
72 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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.
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.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
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.
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.
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.
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-4Who is Mastercard?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
Working pattern and location restrictions need checking in the full posting.
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