Data Engineer

Posted 15 Days Ago
Be an Early Applicant
Hiring Remotely in Lviv, Lviv Oblast
Remote
3-5 Years Experience
Software
The Role
Seeking a Data Engineer to lead a team and modernize a data platform into a cloud-based self-service analytics project. Responsibilities include designing and modeling data into DWH and Data Marts using Spark and MS SQL, collaborating with BI engineers, moving on-premises solutions to the cloud, and more.
Summary Generated by Built In

Company Description

Seeking a Data Engineer to lead a small team and modernize a simple data platform into a cloud-based self-service analytics project.

Sigma Software provides top-quality software development, graphic design, testing, and support services. Systems developed to deliver customer benefits in automotive, telecommunications, aviation, advertising, gaming, banking, real estate, and healthcare industries

It is an Internal Sigma Software project that combines 2 goals: automating reporting and exposing a self-service data analytics system for the company. You will be responsible for designing and modeling data into DWH and Data Marts using Spark and MS SQL, exposing this data to, and collaborating with, BI engineers making reports in Apache Superset as well as other roles consuming such data, moving on-premises solutions to the cloud

Job Description

The goal is to create an efficient system for collecting, processing, analyzing, and visualizing large amounts of data from various sources

  • Lay down the foundation and model the data
  • Develop a platform for building and maintaining data pipelines that collect data from different sources
  • Create Data Warehouse
  • Analyze and prepare domain descriptions in collaboration with Business analytics
  • Create Data Marts
  • Design a permission model with flexible control over vertical and horizontal access to data

Qualifications

  • Conceptual knowledge of data analytics fundamentals, e.g., dimensional modeling, ETL/ELT, reporting tools, data governance, data warehousing, structured and unstructured data
  • Strong SQL knowledge and experience with RDBMS, confident knowledge of database fundamentals
  • Experience in database development and data modeling, ideally with Databricks/Spark
  • Experience with Python
  • Experience with Azure
  • Working knowledge of serialization formats and their trade-offs (columnar vs. row-based)
  • Experience debugging and optimizing Spark jobs
  • Strong written and verbal communication skills
  • At least an Upper-Intermediate level of English
  • BS in Computer Science or a related field

WOULD BE A PLUS

  • Experience with a Business Intelligence tool

Top Skills

Python
Spark
SQL
The Company
New York, New York
1,516 Employees
On-site Workplace

What We Do

Sigma Software Group, an award-winning and trusted IT partner, has been serving customers for over 21 years, providing comprehensive IT solutions to various businesses, ranging from startups to established software product houses. As one of Europe's substantial IT consultancies, it brings together a dedicated workforce of over 2,100 professionals in 40 offices across 19 countries. With a diverse client base, including more than 300 enterprises, including Fortune 500 stalwarts, Sigma Software Group is a preferred choice for developing solutions that help businesses create cutting-edge products while meeting their unique needs.

Sigma Software Group operates as a dynamic ecosystem of tech companies, offering 25 ready-to-implement innovative products and 40+ value-added services. Furthermore, Sigma Software Group is committed to fostering innovation through initiatives such as the Sigma Software Labs business incubator, Sigma Software University, the SID Venture Partners VC Fund, UA Tech Network, Techosystem, the European Business Association, and other collaborative efforts.

Since 2015, Sigma Software Group has consistently earned recognition on the IAOP's prestigious World's Top 100 Outsourcing list. The company's accomplishments have also been acknowledged by prominent global media outlets such as Forbes, CNBC, The Times, and Reuters

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