Middle Data Engineer

N-iX

Województwo mazowieckie

Hybrid

PLN 50,000 - 80,000

Full time

14 days+
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Benefits offered by this job

Flexible working format
Competitive salary and compensation package
Personalized career growth
Professional development tools
Corporate events and team buildings

Job summary

N-iX is looking for a Middle Data Engineer in Poland (Województwo mazowieckie) to design, build, and maintain scalable data systems. The role involves developing data pipelines, ensuring data quality, and working with analytics tools. Candidates should have 2-4 years of Data Engineering experience, strong SQL skills, and proficiency with Snowflake, dbt, and the Azure cloud. The position offers flexible working formats, competitive salary, and professional development opportunities.

Qualifications

  • 2–4 years of experience in Data Engineering or a related role.
  • Solid SQL skills with joins, aggregations, and window functions.
  • Hands-on experience with Azure cloud platform.

Responsibilities

  • Build and maintain data pipelines (batch and near real-time).
  • Develop and optimize data models for analytics and BI tools.
  • Write efficient SQL queries for large-scale datasets.
  • Ensure data quality, integrity, and consistency across systems.

Skills

SQL skills
Data Engineering experience
Snowflake
dbt
Python
ETL/ELT tools

Tools

Azure cloud platform
Docker
Spark

Job description

Our customer is one of the world's largest food and beverage companies, operating in 189 countries with over 2000 brands. The company's diverse portfolio includes products such as bottled water, dairy products, breakfast cereals, coffee, confectionery, frozen food, pet foods, snacks, and baby food.

We are looking for a Middle Data Engineer to design, build, and maintain scalable data systems that support analytics, reporting, and machine learning use cases. This role requires strong ownership, solid SQL skills, and experience working with large datasets in production environments.

Responsibilities
  • Build and maintain data pipelines (batch and near real-time).
  • Develop and optimize data models for analytics and BI tools.
  • Write efficient SQL queries for large-scale datasets.
  • Support development and maintenance of ETL/ELT processes.
  • Ensure data quality, integrity, and consistency across systems.
  • Collaborate with data analysts, data scientists, and product teams to understand data requirements.
  • Monitor and troubleshoot data pipelines and workflows.
  • Contribute to improving the performance of the existing data infrastructure.
  • Work with cloud-based data platforms and modern data stack tools.
Requirements
  • 2–4 years of experience in Data Engineering or a related role.
  • Main technical skills are: Snowflake, dbt, ADF.
  • Solid SQL skills (joins, aggregations, window functions).
  • Understanding of data governance and data quality concepts.
  • Proficiency in Python.
  • Experience with ETL/ELT tools.
  • Hands-on experience with the Azure cloud platform.
  • Azure Ops experience: provisioning and configuring.
  • Experience working with data warehouses (e.g., Snowflake, BigQuery, Redshift).
  • Understanding of data modeling concepts (e.g., star schema).
Nice to have
  • Basic knowledge of Docker or containerization.
  • Experience with data processing frameworks (e.g., Spark).
Soft skills
  • Strong analytical thinking and problem-solving skills.
  • Ability to work independently with some guidance.
  • Good communication skills with technical and non-technical stakeholders.
  • Willingness to learn and grow in a collaborative environment.
We offer
  • Flexible working format - remote, office-based or flexible
  • A competitive salary and good compensation package
  • Personalized career growth
  • Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
  • Active tech communities with regular knowledge sharingEducation reimbursement
  • Memorable anniversary presents
  • Corporate events and team buildings
  • Other location-specific benefits
  • not applicable for freelancers
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