
The Merck Data Engineering Team is responsible for designing, developing, testing, and supporting automated end-to-end data pipelines and applications on Merck’s data management and global analytics platform (Palantir Foundry, Hadoop, AWS and other components).
The Foundry platform comprises multiple different technology stacks, which are hosted on Amazon Web Services (AWS) infrastructure or on-premise Merck’s own data centers. Developing pipelines and applications on Foundry requires:
• Proficiency in SQL / Java / Python (Python required; all 3 not necessary)
• Proficiency in PySpark for distributed computation
• Familiarity with Postgres and ElasticSearch
• Familiarity with HTML, CSS, and JavaScript and basic design/visual competency
• Familiarity with common databases (e.g. JDBC, mySQL, Microsoft SQL). Not all types required
This position will be project based and may work across multiple smaller projects or a single large project utilizing an agile project methodology.
Roles & Responsibilities:
• Develop data pipelines by ingesting various data sources – structured and un-structured – into Palantir Foundry
• Participate in end to end project lifecycle, from requirements analysis to go-live and operations of an application
• Acts as business analyst for developing requirements for Foundry pipelines
• Review code developed by other data engineers and check against platform-specific standards, cross-cutting concerns, coding and configuration standards and functional specification of the pipeline
• Document technical work in a professional and transparent way. Create high quality technical documentation
• Work out the best possible balance between technical feasibility and business requirements (the latter can be quite strict)
• Deploy applications on Foundry platform infrastructure with clearly defined checks
• Implementation of changes and bug fixes via Merck's change management framework and according to system engineering practices (additional training will be provided)
• DevOps project setup following Agile principles (e.g. Scrum)
• Besides working on projects, act as third level support for critical applications; analyze and resolve complex incidents/problems. Debug problems across a full stack of Foundry and code based on Python, Pyspark, and Java
• Work closely with business users, data scientists/analysts to design physical data models

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