Základné
Data Analyst
Zverejnené: 21.05.2026
Termín uzávierky: 05.07.2026
Referencie na pracovnú pozíciu: 30dac7d01d776033c02eaa1e12a1ef8b
Informácie o pracovnej pozícii
Poloha
madrid, Spain
Spoločnosť
JR Spain
Klient / Zamestnávateľ
Antal International
Referencie na pracovnú pozíciu
30dac7d01d776033c02eaa1e12a1ef8b
Typ zápisu
Základné
Vyžaduje sa pracovné povolenie EÚ
Nie
Zverejnené
21.05.2026
Termín uzávierky
05.07.2026
Popis práce
Job Description Requirements: Minimum 2 years of experience as a Data Analyst, preferably in e-commerce or digital environments. Strong analytical mindset, well-organized and highly detail-oriented. Strong proficiency in SQL . Experience in advanced data analysis (exploratory analysis, A/B testing , statistical modeling). Solid skills in data visualization and dashboard creation ( Looker, Power BI, Tableau ). Experience with Python (Pandas) and interest in technologies such as DBT or AI is a plus. Degree in Statistics, Data, Economics or similar (Master’s degree highly valued) Fluent in English/ Spanish Excellent communication skills, able to interact with both technical and business stakeholders. Responsibilities: Perform advanced data analysis to support strategic decision-making. Design, build and maintain business dashboards. Define, monitor and analyze A/B tests in close collaboration with stakeholders. Build and automate data pipelines to enable efficient analysis. Communicate insights and results across the organization. Work closely with Data Science and Data Governance teams. Check Your Resume for Match Upload your resume and our tool will compare it to the requirements for this job like recruiters do.
Zručnosti
analyse big data
apply statistical analysis techniques
Business Analytics
Business Intelligence
cloud technologies
collect ICT data
create data models
Data Engineering
data ethics
Data Mining
Data Models
data quality assessment
Data Science
data storage
data visualisation software
Database
define data quality criteria
deliver visual presentation of data
digital data processing
documentation types
establish data processes
execute analytical mathematical calculations
Game Theory
gather data for forensic purposes
Hadoop
handle data samples
Healthcare Analytics
image recognition
implement data quality processes
Information Architecture
information categorisation
information confidentiality
Information Extraction
information structure
integrate ICT data
interpret current data
LDAP
LINQ
make data-driven decisions
manage cloud data and storage
manage data
manage data collection systems
manage quantitative data
Marketing Analytics
MDX
multidisciplinary research
N1QL
normalise data
online analytical processing
perform data cleansing
perform data mining
query languages
report analysis results
Research Design
resource description framework query language
Social Network Analysis
SPARQL
statistical modeling techniques
Statistics
store digital data and systems
Unstructured Data
use data processing techniques
use databases
use spreadsheets software
visual presentation techniques
Web Analytics
XQuery