Data Analytics Engineer — Hybrid, Growth & Impact

NOBA Bank Group; Stockholms kommun; Hybrid; SEK 550,000 - 750,000; Full time

Benefits offered by this job

Freedom with Responsibility

Career Development

Feedback Culture

Coaching Leadership

Caring Company Culture

Job summary

NOBA Bank Group is seeking a Data Analytics Engineer to advance analytics capabilities, optimize data workflows, and unlock the value of data across the organization. The role sits in the Data & Analytics Engineering department and involves building analytics infrastructure and collaborating with multiple internal teams.

The role offers a hybrid work model with two common in-office days, emphasizing collaboration, learning, and a proactive, can-do approach to data challenges.

Qualifications

• Experience in data or analytics engineering roles.
• Academic degree in analytics engineering or data engineering or related field.
• Proficiency in ETL processes and creating analytics-ready datasets.

Responsibilities

• Design and implement efficient data models for analytics workflows and end-user usability.
• Build robust and scalable data pipelines to support business intelligence and analytics needs.
• Collaborate with Risk, Finance, and IT to ensure data solutions align with business needs.
• Ensure data quality, security, and compliance throughout the analytics lifecycle.
• Drive technical improvements by introducing modern tools and processes to enhance analytics capabilities.
• Partner with other engineers to align transformation processes for analytics purposes.

Skills

English fluency

Swedish/Norwegian fluency

Education

Degree in analytics engineering or data engineering

Tools

Databricks

dbt (SQL)

Python

Power BI

Job description

NOBA Bank Group is seeking a Data Analytics Engineer to advance analytics capabilities, optimize data workflows, and unlock the value of data across the organization. The role sits in the Data & Analytics Engineering department and involves building analytics infrastructure and collaborating with multiple internal teams.

The role offers a hybrid work model with two common in-office days, emphasizing collaboration, learning, and a proactive, can-do approach to data challenges.