Senior Data Engineer at Appodeal

Barcelona, Catalonia, Spain -

Full Time

Start Date

Immediate

Expiry Date

16 Feb, 26

Salary

0.0

Posted On

18 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Pandas, PySpark, Data Lakes, Data Warehouses, Data Orchestration, Dagster, Airflow, Streaming Technologies, Kafka, Spark Structured Streaming, Cloud Platforms, AWS S3, AWS EC2, Problem Solving, Machine Learning, Data Analytics

Industry

IT Services and IT Consulting

Description

Appodeal is a dynamic US-based product company with a truly global presence. We have offices in Warsaw, Barcelona and Virginia along with remote team members located around the world. Our company thrives on diversity, collaboration, and innovation, making us a leader in the mobile app monetization space. Why Appodeal? At Appodeal, we’re more than just a company—we’re a team united by a common mission: to help every person discover and grow their talents! We take pride in our cutting-edge product and our internationally dispersed team of talented professionals. Here’s what we value, and what we hope you do too: Continuous Learning and Growth: We are passionate about learning, growing personally, and building rewarding careers. Making an Impact: We are committed to building a history-defining company that leaves a lasting impact on the mobile app industry. Solving Exciting Challenges: We tackle complex problems every day, supported by a team of world-class professionals and mentors. Enjoying the Journey: We believe in having fun while working toward our goals. We are seeking a skilled Data Engineer to join our MGP (Mobile Growth Platform), UA team in Barcelona. The ideal candidate will be responsible for building, maintaining, and optimizing our data infrastructure, ensuring seamless data flow and accessibility for ML, analytical and business needs. Key Responsibilities Oversee the in-house ML data platform, managing tasks such as collecting, storing, and transforming data to support machine learning models. Design, develop, test, and orchestrate data workflows to streamline pipelines. Establish and promote best practices for data handling and processing within the ML context. Contribute to the development of internal tools for automating data processes and business workflows, enhancing efficiency and scalability. Collaborate closely with product, MLOps and data science teams to ensure an optimal data experience for all ML practitioners and data consumers. Requirements 3-5+ years of professional work experience in data engineering. Strong expertise in Python and common data frameworks (Pandas, PySpark). Experience with modern data storage solutions: Data lakes (Delta tables), and data warehouses. Experience with data orchestration tools (Dagster, Airflow). Experience with streaming technologies (Kafka, Spark structured streaming). Solid understanding of system design, data structures, and algorithms Experience with cloud platforms (AWS S3, EC2 etc.) Strong problem-solving skills and ability to excel in a fast-paced startup environment Basic knowledge of machine learning and data analytics. Basic knowledge of data visualization and BI tools. Based in Barcelona or ready to relocate to Barcelona. Nice to have Experience with Databricks platform. Experience in building ML data platforms. Why Appodeal Work in a fast-growing international AdTech ecosystem. Collaborate with brilliant minds in data science, AI, and engineering. Competitive compensation with performance-based bonuses. Opportunity to make a direct impact on a data-driven company serving millions globally. With an outstanding product and a mission that excites and inspires, Appodeal offers a unique opportunity to make an impact while being part of an amazing team. Join us and help shape the future of mobile app success!

Responsibilities

The Data Engineer will oversee the in-house ML data platform, managing tasks such as collecting, storing, and transforming data to support machine learning models. They will also design, develop, test, and orchestrate data workflows to streamline pipelines and enhance efficiency.