も⁠し⁠か⁠し⁠お⁠あ⁠な⁠た⁠は未⁠来⁠の⁠.⁠.⁠.  Senior Analytics Engineer (Talent Acquisition, People Tech team)

アナリティクスずデヌタサむ゚ンス

Bratislava, Slovakia (Slovak Republic) · Warszawa, Poland · Budapest, Hungary · Stockholm, Sweden · Helsinki, Finland

Full-time

About the Role

Together with our amazing People Analytics teammates from DoorDash, we’re looking for a Senior Analytics Engineer to support our People Tech team and focus on Talent Acquisition analytics.

The role can be based in Finland, Sweden, Greece, Hungary, Poland, Slovakia or Czech Republic. You can work onsite, hybrid, or fully remote from one of the mentioned locations - the work format is up to you 🙌

Your main stakeholder will be our wonderful VP of Talent Acquisition based in Germany. In addition, there will be a team of People Analytics folks from DoorDash based in the US - with them, you’ll have plenty of knowledge-sharing activities, and one of the teammates will become your onboarding buddy. 

Your daily work will include

• Developing reporting and metrics quality as a whole for Wolt’s Talent Acquisition team, leveraging existing Doordash to ensure we’re not reinventing the wheel.

• Working on our centrally maintained data integrations and data pipelines powering our Data Warehouse, our Looker data models, and dashboards. You'll get to utilize our modern BI stack as part of your work (Python, Looker, Snowflake, Airflow, AWS, Kafka, Github).

• Helping our Talent Acquisition team with measuring vital TA metrics, such as recruiter productivity, time to hire, time to fill, candidate diversity, candidate NPS, etc. to enable data-driven insights that drive excellence.

• Diagnose data and reporting needs and build new solutions, invent new, customer-driven approaches to big, ambiguous, critical problems. 

• Cultivate relationships with Talent Acquisition and other People team leaders across the company to develop the next version of our user self-service platform, enabling us to deliver analytics at scale.

What we offer

• Complex environment with tons of data just waiting to be utilized — you’ll get hands-on experience in working on various TA metrics and topics. 

• You can choose the ways of working - work onsite, hybrid, or fully remote from one of the locations mentioned above.

• You would get to work in a company culture where we take ownership beyond the obvious, do common things uncommonly well, think big but stay humble, do right by people, treat others kindly and justly, and recognize that if we don’t learn, we won’t stay still but fall behind and keep in mind that Luke was Yoda’s greatest achievement. Read more about how we work.

応⁠募⁠資⁠栌・条⁠件

• Plenty of experience working as a BI Developer, Analytics Engineer, or techy Data Analyst ideally within Talent Acquisition, Sales, Supply Chain, or Finance domains.

• Strong hands-on experience with data integrations, data pipelines, data models, metric development, and dashboards.

• Tech skills: Python (basic), SQL (advanced), Airflow, Kafka, AWS, and one of the modern BI tools (Tableau, Power BI, Looker, or similar). Advanced SQL skills, and ability to write optimized queries for large data sets.

• Since you’ll be taking care of our internal stakeholders, we’re looking for someone who truly enjoys interacting with people on a daily basis. The ability to search for information and ask relevant questions from various teams will be crucial.

次⁠のス⁠テ⁠ッ⁠プ

The position will be filled as soon as we find the right person, so make sure to apply as soon as you realize you really, really want to join us!

The compensation will be a negotiable combination of monthly pay and DoorDash RSUs. The latter makes it exceptionally easy to be excited about our company growing and doing well, as you’ll own a piece of the pie.

For any further questions about the position, you can turn to Product+ Talent Acquisition Partner - Zhanna Filintseva (zhanna.filintseva@wolt.com)

今⁠す⁠ぐ応⁠募⁠す⁠る

基⁠本⁠情⁠報

添⁠付フ⁠ァ⁠む⁠ル

職⁠務⁠経⁠歎⁠曞⁠ず履⁠歎⁠曞⁠英⁠語⁠を必⁠芁⁠ずす⁠るポ⁠ゞ⁠シ⁠ョ⁠ン⁠に応⁠募⁠す⁠る際⁠は英⁠文⁠のR⁠e⁠s⁠u⁠m⁠e⁠⁠をP⁠D⁠F曞⁠匏⁠に⁠お⁠ご提⁠出⁠を⁠お願⁠い⁠い⁠た⁠し⁠た⁠す⁠。

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    Product: Juan, Data - portrait
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