Staff DataOps Engineer

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Ankorstore

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Ankorstore

Staff DataOps Engineer

United Kingdom

In office

Description

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