Senior Data Infrastructure Engineer
1 day ago
Estimated salary: $170,000 - $250,000 per year.
About MastercardWe are a leading global payments and technology company that makes payments easy, simple, and secure. We support a wide range of digital payments choices, making transactions secure, simple, smart, and accessible.
Data Engineer RoleWe are seeking an experienced Senior Data Infrastructure Engineer to join our Data and Platform team. This pivotal role is responsible for guiding Data Engineer design, supporting multiple Data Analysts and Data Scientists, as well as assisting on various data-driven requests across the company.
Responsibilities- Owning complex problems having dependency across services and facilitating cross-functional team interactions to drive resolution, including large-scale data extraction, transformation, and analysis.
- Writing code to build and enhance applications/services and promoting code-reviews, code scanning, and other standard development practices to deliver high-quality data modeling and artifacts to production.
- Maintaining the tooling and infrastructure that enables our Analysts and Data Scientists to work efficiently and effectively.
- Promoting strategies to improve our data modeling, quality, and architecture.
- Automating and simplifying all aspects of software delivery and development actively evangelizing the need to automate and simplify where needed.
- Supporting production code to produce comprehensive and accurate data artifacts.
- Conducting technical interviews for hiring engineering staff and raising the performance bar.
- Ability to write secure code in three or more languages (e.g., Python, Java, JavaScript, PHP) and familiar with secure coding standards (e.g., OWASP).
- Experience with cloud technologies, especially AWS Redshift, AWS Glue Jobs and Crawler, Lake Formation/CDK Policies, Step Functions, S3, SQS, SNS, and Sparks technology.
- Experienced with streaming data such as Kafka or AWS Kinesis.
- Experience with monitoring tools, such as DataDog, Splunk, AWS Cloud watch/Cloud trails.
- Experience with analysis tools, such as Athena or Tableau.
- Understanding internals of operating systems (Mac, Linux) to write interoperable and performant code.
- Experienced with developing and maintaining data pipelines for the extraction, transformation, and/or loading of large-scale data.
- Experienced with working with large data sets. You've implemented parallel processing and have dealt with the limitations and challenges of working with terabytes of data.
- Able to perform debugging and troubleshooting to analyze core, memory, heap, thread dumps and remove coding errors.
- Skills to document and coach team on the development practices and coding guidelines (e.g., branching, peer reviews, library use, logging, scanning rules, test-driven development, error handling).
- Skills to undertake a technical review of code across applications and their dependencies to look for anti-patterns and promote continuous refactoring.
- Skills to simplify deployment and eliminate software and infrastructure snowflakes using standardized platforms, ephemeral instances, and automation.
- Skills to orchestrate release workflows and pipelines to achieve CI and CD using industry-standard tools (e.g., Jenkins, Bamboo, AWS pipelines, others).
- Able to configure rules and build automation for code with vulnerability scanning and software composition analysis using standard tools (e.g., Codecov).
- Skills to define, organize, and report on test runs for major, minor, and hotfix releases (including unit, component level, system level, customer journeys, past customer issues, and regulatory controls).
- Skills to conduct various performance tests (e.g., load testing).
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