Senior Data Engineer

We are looking for a bright, smart and highly motivated Big Data expert to join our team and project in AdTech domain.

Our client is a technology company building the next generation of advertising products and experiences for premium video. The mission is to provide the best advertising experience for consumers, the best monetization for premium publishers, and the best return for brand advertisers.

The team uses data engineering, data science, big data and full-stack engineering using technologies such as Python/Ruby, Scala/Elixir, SQL, Angular/React, AWS (mostly DynamoDB and Kinesis), Databricks/EMR, Spark and Spark Streaming, Redshift/Athena and high traffic (10GB of streaming data is consumed per day), public APIs. There are hundreds of TBs of data in our data lake.

Responsibilities:

• Build and modify Spark jobs (in Scala) to perform various tasks, from reading Kinesis streams using Spark Streaming, to joining and aggregating huge data sets, to integrating with third party data sources

• Develop and launch new features to adapt to evolving business needs

• Be an active and engaged owner of our data infrastructure

• Be curious and seek to understand all aspects of our business

• Maintain high standards of code quality, and encourage the same by providing constructive code reviews to collaborators

• Troubleshoot and resolve issues, problems, and errors encountered across various

• systems

• Collaborate with Data Science, Product, Research, and Engineering teams to iterate on the roadmap

• Gather requirements when underspecified

Qualifications:

• Strong knowledge with Spark (using Scala)

• Strong knowledge of SQL required

• Working knowledge of serialization formats and their trade-offs (columnar vs row-based)

• Experience debugging and optimizing Spark jobs

• Familiarity with database fundamentals, such as ACID, snowflake schema, normalized/denormalized data

• Must be a strong written and verbal communicator

Preferred Qualification

• Familiarity with columnar database, key-value stores, document stores, stream processing, time series databases, data warehouses, and OLAP

• Experience working with HDFS, S3, GCP and BigQuery

• Familiarity with Data Science tooling in Spark

• Experience in the advertising industry is a plus

• Experience with real-time analytics