Key skills
SparkScalaAWS servicesSQLData infrastructure designData pipelinesAPIs backed by relationship-heavy datasetsData lakesCloud warehousesData storage formatsKnowledge graphsData governance practicesMetadata managementAccess controlsApache IcebergDeltaMachine learning pipelinesCritical evaluationAIMachine LearningData EngineeringAWSCommunicationCollaboration
About this role
Pinterest is a platform that inspires creativity and helps users plan memorable experiences. They are seeking a Data Engineer at tvScientific to implement robust data infrastructure and collaborate with cross-functional teams to evolve core data pipelines and design efficient data solutions.
Responsibilities:
- Design and implement robust data infrastructure in AWS, using Spark with Scala
- Evolve our core data pipelines to efficiently scale for our massive growth
- Store data in optimal engines and formats, matching your designs to our performance needs and cost factors
- Collaborate with our cross-functional teams to design data solutions that meet business needs
- Design and implement knowledge graphs, exposing their functionality both via Batch Processing and APIs
- Leverage and optimize AWS resources while designing for scale
- Collaborate closely with our Data Science and Product teams
- Successful design and implementation of scalable and efficient data infrastructure
- Timely delivery and optimization of data assets and APIs
- High attention to detail in implementation of automated data quality checks
- Effective collaboration with cross-functional teams
Requirements:
- Production data engineering experience
- Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala
- Experience in delivering significant technical initiatives and building reliable, large scale services
- Experience in delivering APIs backed by relationship-heavy datasets
- Familiarity with data lakes, cloud warehouses, and storage formats
- Strong proficiency in AWS services
- Expertise in SQL for data manipulation and extraction
- Excellent written and verbal communication skills
- Bachelor's degree in Computer Science or a related field
- Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
- Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
- High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
- Experience in adtech
- Experience implementing data governance practices, including data quality, metadata management, and access controls
- Strong understanding of privacy-by-design principles and handling of sensitive or regulated data
- Familiarity with data table formats like Apache Iceberg, Delta
- Previous experience building out a Data Engineering function
- Proven experience working closely with Data Science teams on machine learning pipelines