Senior Analytics Engineer (Looker)

About us

GetInData | Part of Xebia is a leading data company working for international Clients, delivering innovative projects related to Data, AI, Cloud, Analytics, MLLLM, and GenAI. The company was founded in 2014 by data engineers and today brings together 120 Data & AI experts. Our Clients are both fastgrowing scaleups and large corporations that are industry leaders. In 2022, we joined forces with Xebia Group to broaden our horizons and bring new international opportunities.

What about the projects we work with?
We run a variety of projects in which our sweepmasters can excel. Advanced Analytics, Data Platforms, Streaming Analytics Platforms, Machine Learning Models, Generative AI and more. We like working with top technologies and opensource solutions for Data & AI and MLAI. In our portfolio, you can find Clients from many industries, e.g., media, ecommerce, retail, fintech, banking, and telcos, such as Truecaller, Spotify, ING, Acast, Volt, Play, and Allegro. You can read some customer stories here.

What else do we do besides working on projects?
We conduct many initiatives like Guilds and Labs and other knowledgesharing initiatives. We build a community around Data & AI, thanks to our conference Big Data Technology Warsaw Summit, meetup Warsaw Data Tech Talks, Radio Data podcast, and DATA Pill newsletter.

Data & AI projects that we run and the companys philosophy of sharing knowledge and ideas in this field make GetInData | Part of Xebia not only a great place to work but also a place that provides you with a real opportunity to boost your career.

If you want to be up to date with the latest news from us, please follow up on our LinkedIn profile.

About role
The Analytics Engineers goal is to manage the entire data value chain, from data sources to business insights.
An Analytics Engineer is responsible for collecting business requirements, modeling data, building data pipelines, creating data visualizations, and helping businesses make decisions based on this data. You can use various technologies covering the full data life cycle and work with different kinds of datasets.
An Analytics Engineer often understands both business and technology and is a good communicator who can help them understand each other. Heshe can turn business requirements into working data products (like reports and analysis), often in cooperation with different stakeholders.

Responsibilities

• Collecting business requirements for various data products (e.g. reports, dashboards, analyses, KPIs)
• Advising on metrics for business performance monitoring
• Building aforementioned data products
• Designing and implementing data models in either SQLdbt or BI tool
• Monitoring, building data pipelines, and implementing data transformations (mostly in SQL)
• Data validation and testing
• Communicating results to the business and helping to use them to make decisions
• Data literacy knowledge sharing
• Staying up to date with the latest trends and best practices in analytics engineering