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Data Engineer

Remote worldwide
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Data Engineer

**About us**

At Ankorstore, we believe that local independent retailers have a great impact on the soul of our cities and villages, and we believe that they will flourish even more if they are provided with great tools and exceptional shopping conditions. With this in mind, we are building the largest marketplace that connects authentic European brands with thousands of independent retailers. We are extremely proud to be able to support these amazing entrepreneurs every day.

Ankorstore was founded in 2019 and has recently closed a $250 million Series C funding. We’ve grown our headcount more than 10x in the last 6 months, from 40 people to over 600, and plan to continue scaling strongly.

We’re moving fast to build the best products for our brands and retailers. In 2022 we plan to triple our engineering team by hiring at least 200 new technical roles. We plan to deepen our expertise in the backend, frontend, mobile, infrastructure, and other areas to help us build out our platform.

**What you will do as a Data Engineer at Ankorstore**

  • Design and build our data mesh platform.
    • Batch layer (Airflow, Stitch, SQL, Spark)
    • Speed layer (Kafka, KafkaStream, KSQL, Kafka Connect)
    • Platform (GCS, BigQuery, Fast API,  K8S, Docker, IAC with Pulumi, Github Action, GCP Cloud Logging & Metrics)
  • Define technical guidelines for Data Users (BI, Data Science, Data Analysts and Squads).

You will be reporting to the Engineering Manager on the following responsibilities: 

  • Collaborate with the Product & Tech teams to find and build the best data solutions to our Brands’ and Retailers’ problems.
  • Collaborate with Business Intelligence, Data Science, Data Analyse and Scraping team to build automated data pipelines
  • Implement new data pipelines and solve issues on our product by writing maintainable, scalable and well-tested code
  • Review pull requests made by other engineers and provide feedback that everybody can learn from
  • Share knowledge with your colleagues and learn from them
  • Help us to define and follow the best data practises
  • Provide support for the code you ship

**Why you should join Ankorstore**

* It's a once in a life-time opportunity to join one of the fastest growing European startups
* Our ambitious, mission-driven team is backed by proven VC funds (Tiger Global, Bain Capital)
* We have strong values, and international culture and work in English only
* Our environment is highly dynamic, we're scaling quickly and currently at a stage where you will be able to shape the future of the organisation
* We have strong people-investment values and offer many exciting career opportunities, locally and internationally.
* Our compensation and benefits are competitive in the market
* We offer the possibility to work remotely, in the office or hybrid across many countries in Europe

**Job requirements**

Must Have:

  • DevOps mindset (CI/CD, Unit test, Monitoring, alerting, IaC)
  • DataEng mindset (pipelines idempotency & commutativity)
  • An experience with Airflow and batch processing
  • An experience on a Cloud Provider (GCP, AWS, Azure)
  • An experience in NoSql column oriented databases (Bigquery, Redshit, Snowflake, ClickHouse...) or a Presto like solution (Athena…)
  • Mastered SQL
  • Mastered Docker
  • Mastered Git
  • English fluent

Should have:

  • Knowledge in Service Oriented Architecture & Event bus
  • Knowledge in Kafka ecosystem (Schema registry, kafka connect, debezium…)
  • An experience with Elasticsearch to build a website search solution
  • An experience with Stream proccessing (kafkaStream, Ksql, Flink, SparkStream)
  • An experience with Spark & parquet (Hadoop)

Nice to Have:

  • Knowledge in NoSql database
  • Knowledge in K8S
  • An experience with Lakehouse solution (deltalake, hudi)
  • An experience with an IaC solution (Terraform, Pulumi, CloudFormation…)

*Recruitment process**

* 1st call with the Talent Acquisition Partner
* 2nd call with the Technical Team
* 3rd call with the Engineering Manager


Apply now