Data Engineer (Mid/Senior)

Talon.One GmbH
12 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Remote

Tech stack

API
Airflow
Business Logic
Big Data
Google BigQuery
CSS
Information Engineering
Data Infrastructure
Data Warehousing
DevOps
PostgreSQL
DataOps
TypeScript
Web Applications
Google Cloud Platform
Data Ingestion
React
Kubernetes
Hashicorp
Kafka
Terraform
Docker

Job description

As a Data Engineer / Data Ops, you will be responsible for all engineering tasks related to the infrastructure, data ingestion and DWH pipelines. You will own our data ingestion workflows (currently based on a Kafka stream) and ensure that large-scale data from our PostgresDB instances is continuously and reliably ingested live into BigQuery. You will manage our overall DWH infrastructure, recommend improvements and make sure to always follow best practices. Finally, you will also be involved in Data Engineering pipelines, assisting in the modelling of various data sources helping all departments within the company to make better decisions., * Own the data ingestion streams for all of our client's DBs, from Postgres to BigQuery.

  • Own the overall data infrastructure: Set up, maintain and improve our stack with new technologies for more efficiency and best practices. E.g. advanced DWH pipeline scheduling.
  • Write DWH pipelines and improve our overall DWH code to apply best practices and bring more efficiency.
  • Be part of a data team composed of various profiles, be at the center of all infrastructure decisions and work closely with other stakeholders from the R&D department, especially the DevOps team., * Google Cloud Platform (GKE, Cloud Functions, Pub/Sub and many more)
  • PostgreSQL
  • ArgoCD and helm charts for GitOps and delivery
  • Hashicorp ecosystem (Terraform, Vault, etc…)
  • Kafka and BigQuery for DataOps
  • Go for our API & Custom Kubernetes Operators
  • React.js, TypeScript and CSS modules for our web application

Requirements

Do you have experience in TypeScript?, * 3 - 5+ years of experience in the Data Engineering / Data Ops field, ideally working on big data warehouse projects.

  • You are familiar with the modern data stack and are able to recommend, set up and maintain all different kinds of components from Data ingestion to automation.
  • You have experience with a wide range of tools and technologies within the modern data stack: Kafka, Airflow, DBT Core, BigQuery, Lambda functions etc.
  • You have experience with general infrastructure / DevOps management technologies: Kubernetes, Docker, Postgres, GCP etc.
  • You always thrive for applying data engineering best practices: consistency checks, testing data reliability, monitoring on top of ingestion pipelines, no double business logic in the code.

Benefits & conditions

  • A Research and Development Department of 100+ of engineers, product managers and product designers in Berlin
  • Leaders with 8+ years of experience building our promotions engine
  • €1,000 annual learning budget, full LinkedIn Learning access, and free German language courses to boost your skills
  • 30 days of annual leave, plus extra paid days for your birthday and moving day
  • Home office setup budget, a monthly home office allowance
  • Freedom to work from abroad for up to 90 days worldwide!
  • Mental health support with nilo.health and a discounted Urban Sports Club membership
  • 20% company subsidy on your pension contributions
  • BVG public transport ticket and welcome your furry friend in our dog-friendly Berlin office
  • Lease your ideal bike through BusinessBike

About the company

* The right attitude: modern methods and a diverse, creative workspace with an open and international culture * Everyone for the product: Together we create a flexible, highly scalable product with state-of-the-art technologies. We can only succeed if everyone works as a team * Healthy Growth: Growing our company means growing everyone in the team. We love to share knowledge and learn * A great environment: Flexible and family-friendly environment, bright and easily accessible offices, modern software and hardware * High flexibility degree: Prefer to work early or late at night? Do you have to pick up your children from kindergarten? Do you prefer working abroad? We believe in results and motivated employees

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