Data Engineering Team Lead with AI/ML Focus

10 hours ago


Stockholm, Stockholm, Sweden SeenThis Full time

We are seeking a highly experienced Data Engineer to lead our team in implementing and maintaining our data architecture. This is an excellent opportunity for someone who wants to work hands-on, close to code, and likes to see direct results of their work.

About the Role

The ideal candidate will have 5+ years of experience as a ML Engineer, Data Scientist, or Data Engineer, with a strong understanding of big data technologies, high-volume real-time data processing, and ETL processes. They should be familiar with modern tools for data collection and aggregation, such as Python, SQL, Kubernetes, and Docker.

As a Lead Data Engineer, you will be responsible for taking ownership of diverse data projects, including AI/ML implementations, and collaborating effectively with stakeholders to ensure alignment between data solutions and business objectives. You will also mentor and guide other members of the data engineering team, making technical decisions, and prioritizing tasks.

You will work on maintaining, optimizing, and scaling our existing data pipelines to meet evolving business needs, using your expertise to balance maintenance of existing systems with innovation and improvement.

A relevant degree in engineering or similar, along with professional language proficiency and communication skills in English, are essential for this role. Familiarity with AI/ML concepts and experience in deploying models to production environments are nice to have.

What We Offer
  • An estimated salary range of $180,000 - $220,000 per year, depending on location and experience
  • A dynamic and growing company that values innovation and collaboration
  • A competitive benefits package, including health insurance, retirement plans, and paid time off
About Us

We are SeenThis, a rapidly scaling product company that is shaping the future direction of our data team. We believe in creating a holistic and inclusive data environment, where data points such as video metrics, impressions, and data transfer efficiency can help lower our customers' carbon footprint.



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