DSP - Data Engineer

Responsibilities

Design, implement, and manage end-to-end data pipelines (ETL, data streaming, and warehousing) to ensure data is easily accessible for analysis.
Integrate with third-party APIs for accessing external data
Create and maintain data warehouses for reporting or analysis
Consult and partner with engineering and product teams to execute data-related product initiatives
Evaluate existing tools/solutions for every new use case and build one if necessary
Willingness to take end to end ownership and being accountable for the success of the product.
Experience in architecting & building real-time data pipelines.
Break down business requirements into technical solutions at global scale

At least have 3 years of experience in Data Engineering role
Ability to write clean and structured in SQL, bash scripts, and Python (or similar languages)
Solid understanding of database technologies
Experience in building automated, scalable, and robust data processing systems
Experience with building ETL, data warehouse systems (e.g. Athena/Bigquery) and batch/semi-online building blocks (e.g. MapReduce, Spark)
Experience in working with large scale quantitative data using Spark or similar technologies
Ability to quickly resolve performance and systems incidents
Big Data/ML experience is a plus
Experience with RTB, Google IMA SDK, VAST, VPAID, Header bidding is a plus
Past experience in product companies would be a big plus.

All your information will be kept confidential according to EEO guidelines.

See also