LEAD DATA ENGINEER

1 Month ago • 5 Years + • Data Analyst

About the job

Job Description

As a Lead Data Engineer, you will be responsible for developing an infrastructure for solving product analytics problems based on ClickHouse. You will also build and support data processing pipelines using the Spark on Kubernetes stack, Airflow, Clickhouse, and Python. You will be responsible for prioritizing tasks for a mini-team of data engineers, optimizing infrastructure, helping analysts build complex data processing pipelines, and organizing processes for systematic data collection from different sources. You will be working with a variety of technologies, including Airflow, Spark, Kubernetes, AWS S3, ClickHouse, PostgreSQL, MySQL, Scala, Python, and SQL. You will also be involved in data governance and CI/CD processes.
Must have:
  • 5+ years of experience as a Data Engineer
  • Experience building ETL on Apache Spark
  • Understanding of Apache Airflow orchestration
  • Knowledge of SQL and Python
  • Experience with AWS S3
  • Experience with ClickHouse, PostgreSQL, and MySQL
  • Fluent Russian
Perks:
  • Relocation to Serbia, Armenia, or other destinations
  • Relocation program and assistance with paperwork
  • Competitive salary reviewed every 6 months
  • Flexible work setup
  • Flexible benefits: $1000 annual perk allowance
  • Full pay during sick leaves and personal leaves
  • 20 working days of vacation annually
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Our team values ​​an analytical approach to decision making. We accumulate a huge amount of data every day – game events, marketing metrics and much more, which, when carefully analyzed, helps us get valuable insights and improve our games. High quality and speed of processing of this data play a key role for us. And we are looking for an experienced Lead Data Engineer who will help us with this and will be able to take our work with data to the next level.

What we will trust you with

  • Development of an infrastructure for solving product analytics problems based on ClickHouse.
  • Building and supporting data processing pipelines on the Spark on Kubernetes stack (Scala and SQL API), Airflow, Clickhouse and Python.
  • Prioritize tasks for mini-team of data engineers.
  • Optimization of infrastructure (optimal selection of memory size, cores, disks, instance types) for data processing tasks.
  • Helping analysts build complex data processing pipelines in Airflow.
  • Organization of processes for systematic data collection from different sources using different protocols.

Our stack:

  • Orchestration - AirFlow v2.5.3
  • ETL - Spark v3.2.0, AWS Glue
  • Resource Management - Kubernetes
  • Storage - AWS S3
  • DB - ClickHouse, PostgreSQL, MySQL
  • Languages - Scala, Python, SQL
  • Data governance - DataHub
  • DQ - Deequ
  • CI CD - GitLab CI
  • Secret storage - Vault
  • BI - Tableau

What we expect from you

  • Experience as a Data Engineer or similar position for at least five years.
  • Ability to build ETL on Apache Spark.
  • Understanding of how to implement orchestration on Apache Airflow.
  • Knowledge of SQL and the ability to understand Python code.
  • Experience working with S3.
  • Experience in working with databases (ClickHouse - must have, PostgreSQL, MySQL) and query optimization.
  • Fluent Russian.

WHAT WE OFFER

  • An opportunity to contribute significantly to a globally successful project within a stable international company.
  • Relocation to Serbia, or Armenia, or another destination upon our mutual agreement.
  • Relocation program and assistance with paperwork for residence in countries where our offices are located.
  • Competitive salary, reviewed every 6 months based on market trends and your performance.
  • Flexible work setup: whether you prefer coming to the office, working from home, or a hybrid of the two, the choice is yours.
  • Flexible benefits: an annual $1000 to spend on perks, including health insurance, sports, therapy, education and language classes.
  • Full pay during sick leaves and personal leaves, in addition to 20 working days of vacation annually.
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