Staff DataOps Engineer

About us 

We are in business to save independent retail in Europe!

Across our towns and city centres, unique neighbourhood shops have been overshadowed by large chains and e-commerce giants. To combat this, we’ve created a BtoB wholesale marketplace designed to help independent retailers to compete against larger competitors and thus maintain a connected community of stores, brands and shoppers in the places we live.

Established in 2019 in France, we’ve since expanded to other European countries, including Spain, Germany, UK and the Netherlands. Driven by our commitment to customer satisfaction, we constantly innovate to develop cutting-edge tools and services that set new standards in the market.

Get in touch if you are looking to join a purpose-driven, international team that revolutionizes an old-fashioned industry!

Together Let’s Rewild Retail! 

The Team :

The Analytics and Data engineering team is responsible for maintaining Ankorstore's data platform.

Data is used for analysis and reporting purposes, and more recently for business, in Production, processes. As a result, the platform reliability and robustness is more critical than ever, and an acceleration in our deployment phases from DS/DA contributions (scores, calculated features) to Production is needed.

Main responsibilities :

The Staff Data Ops Engineer we are searching for will have a wide-ranging and intricate array of duties, necessitating a profound technical and business acumen in deploying data pipelines, overseeing costs, enhancing system reliability, and acting as the primary expert for dataOps processes in a collaborative environment, thereby aligning data operations while overarching company goals.

Their scope of influence will spread toward Tech leaders, be able to partner, challenge and recommend data architecture orientations (with a profound problem-solving and frugal - “more value with less resource” - mindset) to serve our most ambitious and complex ML use cases that support our end user experience.

As a pivotal player, the Staff Data Ops Engineer spearheads the accurate and efficient flow of data across the organization and toward Production, autonomously innovating, arbitrating and deciding on data product designs and improvements that significantly impact our end users, by providing a top notch marketplace experience.

The critical role and independent expertise will especially but not only :

• Create and maintain high-complexity data ingestion and distribution pipelines (batch or streaming)

• Create and maintain data exposure pipelines (API endpoints, exports)

• Improve reliability and scalability with monitoring and alerting

• Improve CI/CD and infra as code capabilities

• Test new tools to enrich our platform capabilities

• Monitor platform costs

• Maintain documentation

• Collaborate, be able to challenge, partner, and liaise with Platform team and Data science team

• be the goto person for hot data Ingestion, enrichment and distribution, in the context of prod-ready real-time endpoints served in Production (features, personalization, scoring) 

• Design and built data products with the contribution of DA / DS colleagues, or by your own

• Offer business and stakeholder teams access to product data at scale 

• Contribute to the definition, design, and implementation of data domains

Current stack : GCP, Docker, Kubernetes, Kafka, Airflow, Pulumi, DBT, Bigquery, Sigma, Hightouch

Requirements :

• At least 6 years of experience around Data

• DevOps mindset (CI/CD, Unit test, Monitoring, alerting, IaC)

• DataEng mindset (pipelines idempotency & commutativity)

• Deep knowledge of batch and streaming ingestion tools (especially GCP (inc PubSub, Dataflow)) 

• Mastered K8S

• Mastered Docker

• Mastered Git

• Mastered Python

• Knowledge of CI/CD and IAC tools

Other qualifications that would add value :

• Experience with a cloud platform

• Experience with a cloud database (Snowflake, BigQuery, Redshift, etc)

• Extensive experience with GCP

Ankorstore is proud to be an equal opportunity workplace dedicated to promoting diversity. We don’t discriminate based on race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability status.