Position: Data Engineer
Company: V.I.Tech
Category: Data Science
Experience required: 2y
English level: intermediate

The project we work on is in the field of surrogacy, helping to create a world where everyone who wants to be a parent, can. This is achieved through providing services to connect egg donors, gestational carriers, and intended parents and helping them to create a family
The goal of this specific part of the project is to improve daily business decisions through better business performance tracking by various segments. Live dashboards will be created to measure the performance of departments and individuals, knowing where the company stands relative to the goals that were set. The project includes
Consolidation of data sources and making the data influx consistent
Building a single source of truth with standardized data model and data organization
Standardizing the definition of collected metrics
Creating live dashboards and forecasts.

*Requirements*
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL)
Experience building and optimizing data pipelines, architectures and data sets
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
Strong analytic skills related to working with unstructured datasets
Experience with Python
Experience with Keboola is a huge plus

*Responsibilities*
Create a pipeline architecture
Assemble large, complex data sets that meet functional / non-functional business requirements
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python and Keboola
Build analytics dashboards that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics
Help internal teams access clean data from various data sources
Be a strong advocate for maintaining high quality data management practices
Integrate up-and-coming data management and software engineering technologies into existing data structures