Join our dynamic Data & ML Engineering team in iAds and play a pivotal role in driving data solutions that empower data science, finance, analytics, and R&D teams. As an Experienced Data Engineer, you'll work with cutting-edge technologies to design scalable pipelines, ensure data quality, and process billions of data points into actionable insights.
Success Indicators
In the short term, success means delivering reliable, high-performance data pipelines and ensuring data quality across the product. Long-term, you'll be instrumental in optimizing workflows, enabling self-serve analytics platforms, and supporting strategic decisions through impactful data solutions.
Impact
Your work will directly fuel business decisions, improve data accessibility and reliability, and contribute to the team's ability to handle massive-scale data challenges. You'll help shape the future of data engineering within a global, fast-paced environment.
Benefits and Opportunities
You'll collaborate with talented, passionate teammates, work on exciting projects with cutting-edge technologies, and have opportunities for professional growth. Competitive compensation, comprehensive benefits, and an inclusive culture make this role a chance to thrive and make a global impact.
What you'll be doing
Designing and developing scalable data pipelines and ETL processes to process massive amounts of structured and unstructured data.
Collaborating with cross-functional teams (data science, finance, analytics, and R&D) to deliver actionable data solutions tailored to their needs.
Building and maintaining tools and frameworks to monitor and improve data quality across the product.
Providing tools and insights that empower product teams with real-time analytics and data-driven decision-making capabilities.
Optimizing data workflows and architectures for performance, scalability, and cost efficiency using cutting-edge technologies like Apache Spark and Flink.
Requirements: What we're looking for
4+ yeasrs of experience as a Data Engineer
Expertise in designing and developing scalable data pipelines, ETL processes, and data architectures.
Proficiency in Python and SQL, with hands-on experience in big data technologies like Apache Spark and Hadoop.
Advanced knowledge of cloud platforms (AWS, Azure, or GCP) and their associated data services.
Experience working with Imply and Apache Druid for real-time analytics and query optimization.
Strong analytical skills and ability to quickly learn and adapt to new technologies and tools.
You might also have
Hands-on experience with stream-processing frameworks like Apache Flink and Kafka for real-time data integration and analytics.
Knowledge of functional programming concepts, particularly using Scala.
Familiarity with data visualization tools like Tableau or Power BI for creating impactful dashboards.
Experience with machine learning frameworks or building ML pipelines and MLOps workflows.
Previous exposure to ad-tech data solutions or working within ad-serving ecosystems.
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