Do you have experience in data engineering and a growing interest in AI / Machine Learning? Are you ready to take the next step as a lead in a rapidly scaling product company, shaping the future direction of our data team.

Join SeenThis as our Lead Data Engineer!

About the role

We're seeking a Lead Data Engineer to maintain and evolve our high-performance data stack. You'll be at the forefront of implementing best practices and driving innovation in our data architecture.

Our monthly data preprocessing volume is far from ordinary. One of our key data warehouse tables alone streams over 50 billion data points each month, and this number is continually rising.

Most of our workflows are developed using Python and SQL, with data orchestration handled through Luigi, Docker, and Kubernetes all within the Google Cloud Platform (GCP).

You will have to collaborate across various departments, you'll handle commercial, financial, and product data to create a holistic and inclusive data environment. For example, we measure product and technology performance with data points such as video metrics, impressions, and data transfer efficiency, which, in the long run, could be used to help lower our customers’ carbon footprint.

Who we are looking for:

• Someone who wants to work hands-on, close to code, and likes to see direct results of their work

• Lead and nurture a growing data team, including Data Analysts and Data Engineers

• Mentor and guide other members of the data engineering team

• Technical decisions/prioritization going forward

• Take ownership of diverse data projects, including AI/ML implementations

• Maintain, optimize, and scale our existing data pipelines to meet evolving business needs

• Collaborate effectively with stakeholders, ensuring alignment between data solutions and business objectives

We believe you have:

• Relevant education with a degree in engineering or similar

• 5+ years of experience as an ML Engineer, Data Scientist, Data Engineer, or similar positions

• Experience in modern tools for data collection and aggregation

• Extensive experience with Python and SQL in data engineering contexts

• Good understanding of Kubernetes and Docker

• Proven track record working with big data technologies and high-volume, real-time data processing

• Strong understanding of data modeling, ETL processes, and data warehousing concepts

• Ability to balance maintenance of existing systems with innovation and improvement

• Professional language proficiency and communication skills in verbal and written English

Nice to have:

• Familiarity with AI/ML concepts and experience in deploying models to production environments

• Knowledge of model serving and monitoring in production

• Working proficiency and communication skills in verbal and written Swedish