Middle Data Analytics Engineer

NCube Ltd.; United States; Remote; USD 120,000 - 170,000; Full time

Benefits offered by this job

Vacation days

Sick leave

National holidays off

Medical reimbursement

Direct customer collaboration

Professional skill development

Team activities

Volunteer culture support

Job summary

NCube Ltd. is seeking an Analytics Engineer to build data pipelines and models in a scalable data warehouse, enabling cross-functional teams to access data with the required level of detail.

You will collaborate with product and business teams to translate initiatives into data requirements, implement dbt and Airflow-based workflows, and help foster a self-serve analytics culture across the organization.

Qualifications

• 2+ years of experience in SQL and data warehousing
• 2+ years of hands-on experience with dbt core and Airflow in production environments (mandatory)
• 1+ years of experience with reporting/visualization tools such as Tableau, Looker, or equivalent
• Experience with Python and data libraries (pandas, numpy, matplotlib) is a plus
• Ability to foster a self-serve data culture and empower cross-functional teams with data
• Strong communication skills in English; able to translate complex data topics to technical and non-technical stakeholders

Responsibilities

• Build data pipelines and model data in the data warehouse for cross-business access
• Lead data projects from requirement gathering to adoption of data assets
• Translate business developments into technical/data needs
• Propose improvements to data models and collaborate with Data Platform team
• Work with analysts to build scalable reporting and document metrics and definitions

Skills

SQL

Data Warehousing

Communication skills

English proficiency

Self-serve data culture

Tools

dbt core

Airflow

Tableau

Looker

Python

pandas

numpy

matplotlib

AWS S3

Redshift

Job description

We are seeking a Data Engineer for a leading tech-enabled logistics platform that transforms on-demand delivery across sectors like food, grocery, and retail. Operating in over 130 cities across Europe, they are connecting businesses with a network of independent couriers, providing access to fast, flexible, and efficient deliveries.

A goal is to create a modern standard for urban deliveries that addresses environmental and social challenges while providing a premium delivery experience through speed, flexibility, and convenience.

The team is focused on developing a strong data-driven decision-making culture by improving the availability, reliability, and accessibility of data across teams and countries. The objective is to reduce time-to-insight and enable better business decisions through scalable analytics solutions.

As an Analytics Engineer, the role involves working closely with key products and business initiatives from a data perspective. Responsibilities include building high-quality data pipelines and analytical models, applying software engineering best practices to analytics workflows using dbt, and maintaining well-tested and documented data models within the data warehouse.

The position also contributes to the development of a self-serve data culture, helping teams independently access and analyze data through appropriate tools and scalable analytics infrastructure.

Requirements:

• 2+ years of experience in SQL and data warehousing
• 2+ years of hands-on experience with dbt core and Airflow in production environments (mandatory)
• 1+ years of experience working with reporting and data visualization tools such as Tableau, Looker, or equivalent
• Experience with Python and key data libraries (e.g. pandas, numpy, matplotlib) is a plus
• Ability to foster a self-serve data culture and empower cross-functional teams with data
• Strong communication skills in English; capable of translating complex data topics to both technical and non-technical stakeholders
• Our Data stack is made up of AWS S3, Redshift, Airbyte, dbt, Airflow, Castor and Superset.

Responsibilities:

• Build data pipelines and model data in our data warehouse, to allow anyone across the business to interact with data in the level of detail they need
• Lead data projects from start-to-end, from requirement gathering to fostering adoption of the newly created data assets
• Understand the developments in the business, and translate them to technical / data needs
• Propose improvements to our data models and work together with the Data Platform team to improve our data toolkit
• Work together with our analysts to build scalable reporting. Foster data discovery and strengthen data knowledge across the company by writing comprehensive documentation and metrics definitions.

We offer:

• Vacation (up to 20 working days)
• Sick leaves (10 working days)
• National Holidays as time off (up to 11 days)
• Medical reimbursement/insurance after 3 months
• Direct cooperation with the customer
• Communication with Top/Senior level specialists to strengthen your hard skills
• Online/offline teambuildings
• Volunteering culture development and support.