Data Engineer (Postgres/Spark/Elasticsearch, Ukraine) #14738

Purpose Of The Job

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same. We are looking for a savvy Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler, who enjoys optimizing data systems and building them from the ground up. 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.

Main Tasks And Responsibilities

Create and maintain optimal data pipeline architecture.

Assemble large, complete data sets that meet functional / non-functional business requirements.

Identify, design and implement 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 AWS 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.

Education, Skills And Experience

MUST HAVE:

5+ years of experience in a Data Engineer role

Experience working with relational databases and data warehouses, including Postgres, Microsoft SQL Server, Oracle, GCP BigQuery, etc.

Experience with big data tools: Hadoop, Spark, Hive, HBase, etc.

Experience with NoSQL data repositories, ideally, Elasticsearch.

Experience building and optimizing big data pipelines, architectures, and data sets.

Familiarity with workflow management tools: NiFi, Airflow, etc.

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