Ukraine Job Openings
Capgemini Engineering
Data Engineer (Python/Hadoop/Spark, Ukraine)
December 2, 2024
The Data Engineer will support our software developers, database architects, data analysts, and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited about the prospect of optimizing or even re-designing our company's data architecture to support our net generation of products and data initiatives.
- Create and maintain optimal data pipeline architecture,
- Assemble large, complete data sets that meet functional / non-functional business requirements. Identified, designed, and implemented internal process improvements: automating manual processes,
- optimizing data delivery, re-designing infrastructure for greater scalability, performance, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and big data technologies. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, revenue management, operational efficiencies, and other key business performance metrics. Work with stakeholders including the Executive, Product, Data, and Design teams to assist with
- data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our offerings.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Other duties as assigned:
- 5+ years of experience in a Data Engineer role
- Must have Experience working with relational databases and data warehouses, including Postgres, Microsoft
- SQL Server, Oracle, etc.
- Experience with big data tools: Hadoop, Spark, Hive, HBase, etc.
- Experience with No SQL data repositories, ideally, Elastic Search.
- Experience building and optimizing big data pipelines, architectures, and data sets. Familiar with workflow management tools: Ni Fi, Airflow, etc.
- c.
- Must have experience with stream-processing systems, such as Apache Spark and/or Kafka Streaming, Storm, etc.
- Must have Experience with programming and scripting languages: Python, Scala, OOP
- GCP Big Query will be a big plus
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