Position: Middle/Senior Data Engineer (AdTech Platform Development)
Company: Sigma Software
Experience required: 3y
English level: upper

CUSTOMER
Our customer is a US-based technology company that builds the next generation of advertising products and premium video experiences.

The company pioneered the engagement-based ad model and now delivers effective advertising for on-demand, interactive media. Having a solid belief that ads should be enabling rather than interruptive, it has built the definitive engagement advertising system around the core product. The latter one delivers on the promise of “zero waste” advertising. Thus, our customer provides the best advertising experience for consumers, the best monetization for premium publishers, and the best return for brand advertisers.

PROJECT
As a Data Engineer, you will be an important part of the team that owns our data infrastructure. This is no small responsibility, as an AdTech company, data is a lifeblood, and there is a lot of it. Suppose you are excited by and have experience in ingesting, processing, storing, analyzing, and working in a Big Data environment. In that case, you are very likely the one to enjoy this role too!7

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 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
Gather requirements when underspecified

REQUIREMENTS
BS in Computer Science or related field
Strong knowledge of SQL
Strong knowledge of Spark (using Scala)
Experience debugging and optimizing Spark jobs
Working knowledge of serialization formats and their trade-offs (columnar vs. row-based)
Familiarity with database fundamentals, such as ACID, Snowflake schema, normalized/denormalized data
Upper-Intermediate level of English

WOULD BE A PLUS:
Familiarity with the columnar database, key-value stores, document stores, stream processing, time-series databases, data warehouses, and OLAP
Experience working with HDFS and S3
Familiarity with Data Science tooling in Spark
Experience in the advertising industry is a plus
Experience with real-time analytics