Data Platform Architect

Reference:

VAC-7

Sector:

Data Engineering, Data Science, Development, E-commerce

Salary:

Salary negotiable

Town/City:

Berlin

Contract Type:

Full Time

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Practice Manager - Data Science, Machine Learning, AI & Analytics; Collaborator

As a Data Platform Architect, you will be responsible for building, scaling and architecting one of the largest big data platforms in ecommerce. You will develop big data solutions, services, and messaging frameworks to help us continuously process our data faster and more efficiently. You will challenge our status quo and help us define best practices for how we work. And you will have the freedom to launch your own open source projects, contribute to others’ projects, build internal community around your interests, and strengthen your personal brand—while receiving meaningful support at every step.

What you'll do

  • Design and build a cloud-based mass data-processing and log data-processing architecture that will supplement our existing analytics and data warehouse (DWH) architecture
  • Align multiple teams to apply new big data solutions and provide support as an architect and a peer review partner
  • Help evaluate and push for the adoption of technologies that are best suited for specific projects
  • Share your knowledge via documentation, coaching, code reviews, articles and tech talks
  • Demonstrate excellent communication skills and act as a liaison between your team and others

What you'll bring

  • Experience as data architect or senior engineer in larger scale companies in the internet domain like e-commerce, software or infrastructure as a service (SaaS, PaaS), or similar
  • Ability to demonstrate competencies and experience working on time-critical, mass data-processing, parallel data-processing and database initiatives
  • Deep knowledge of big data technologies, like Spark, Flink, Google BigQuery, Presto, Hadoop / MapReduce
  • A passion for working with SQL (e.g. PostgreSQL) and NoSQL (e.g. Cassandra, Redis) databases and scalable pub/sub event message queues (e.g. Kafka, Kinesis)
  • Solid knowledge of data structures and applied data mining and machine learning techniques
  • Knowledge of microservice based SOA and service communication using RESTful APIs, GraphQL, gRPC, Avro or other techniques
  • Solid understanding of data warehouse design and ETL/ELT processing
  • Fluency in at least one programming language, such as Java, Scala or Python
  • Peerless analytical and critical thinking skills and ability to balance technical trade-offs
  • A creative thinker who values accountability, goal-setting and focusing on solutions instead of problems
  • A great communicator with different stakeholders who is skilled in architecture documentation and technical presentations
  • A university degree in Computer Science, Mathematics, Statistics or comparable subject, with an academic record of high achievement
  • English language fluency

 

Talk to us
Practice Manager - Data Science, Machine Learning, AI & Analytics; Collaborator