Senior Snowflake Engineer

Data EngineeringRemote, Iasi, Romania


Description

Position at Ness Romania SRL

Job ID 6803

Why Ness

We know that people are our greatest asset. Our staff’s professionalism, innovation, teamwork, and dedication to excellence have helped us become one of the world’s leading technology companies. It is these qualities that are vital to our continued success. As a Ness employee, you will be working on products and platforms for some of the most innovative software companies in the world.

You’ll gain knowledge working alongside other highly skilled professionals that will help accelerate your career progression. 

You’ll also benefit from an array of advantages like access to trainings and certifications, bonuses, and aids, socializing activities, and attractive compensation.

Requirements and responsibilities

We are looking for a Senior Data Engineer to join Ness Digital Engineering and play a key role in building the foundation of a new data engineering capability for one of our major clients in the US, a global telecommunications and network infrastructure provider.

In this role, you will contribute to the design and implementation of an internal portal, focusing on integrating critical data from device and SaaS data sources into scalable data lakes and Snowflake-based architectures.
You will work closely with stakeholders across multiple teams and business domains, driving alignment and consistency of data models and requirements across core initiatives.

What you’ll do

  • Design, build, and maintain data integration pipelines to collect and consolidate data from multiple devices and SaaS sources into centralized data lakes.
  • Develop data models following the eTOM SID framework, ensuring standardization and consistency for data coming from acquired or merged entities.
  • Collaborate with business stakeholders to analyze and document Business Requirements Documents (BRDs) for cross-functional strategic initiatives.
  • Build and maintain scalable data architectures and ETL/ELT pipelines with a strong focus on performance, quality, and cost efficiency.
  • Optimize Snowflake data warehouse usage for both cost and query performance (clustering, caching, query tuning).
  • Develop data models around stated use cases to capture key business metrics (KPIs) and data transformations.
  • Validate and test data models and pipelines to ensure reliability and accuracy.
  • Document solutions, standards, and best practices, and support knowledge transfer within the team.
  • Work closely with product, architecture, and business teams to ensure alignment between business requirements and the technical data solutions.
  • Contribute to establishing data governance and security best practices within the data platform.

What you’ll bring

  • 5+ years of experience in data engineering or data analytics roles;
  • Strong expertise in Snowflake (warehousing, data modeling, performance optimization);
  • Experience building and managing data lakes and ETL/ELT pipelines;
  • Advanced SQL and proficiency with Python / Bash / other scripting languages;
  • Familiarity with eTOM SID data modeling or other enterprise data modeling frameworks;
  • Hands-on experience with cloud platforms (AWS / GCP preferred);
  • Familiarity with developer workflows (Git/GitHub, CLI, SSH);
  • Ability to gather, structure, and maintain Business Requirements Documents (BRDs) and work directly with non-technical stakeholders;
  • Previous experience working in telecommunications or large-scale enterprise environments (preferred);
  • Understanding of data governance, security, and compliance requirements.

Not checking every single requirement?

If this role sounds good to you, even if you don’t meet every single bullet point in the job description, we encourage you to apply anyway. For most of the candidates who applied, we found a role that was a very good fit with their skills.

Let’s meet, and you may just be the right candidate for one of our roles.

At Ness Digital Engineering we are willing to build a work culture that is based on diversification, inclusion, and authenticity.