Data Analytics Engineer

Sólo para miembros registrados
Barcelona, Spain
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
€ 65K

Job location

Barcelona, Spain

Tech stack

Amazon Web Services (AWS)
Big Data
Cloud Computing
Continuous Integration
Data Infrastructure
Data Warehousing
DevOps
Python
Redis
SQL Databases
Data Processing
Snowflake
GIT
Containerization
Kubernetes
Data Pipelines
Docker

Job description

A leading chat marketing platform in Barcelona is seeking a motivated Data Engineer to join their Data team. The role involves designing scalable data pipelines, ensuring data quality and security, and collaborating with cross-functional teams to unlock new insights. Ideal candidates will have strong experience in SQL and Python, with a focus on transforming data for analytics and decision-making. This position offers a hybrid work model, health insurance, and various professional development benefits.

Requirements

  • Proven experience in Analytics Engineering, Data Engineering or a related role.
  • Strong experience with SQL for querying and optimization of large datasets.
  • Strong proficiency in Python for data processing.
  • Strong understanding of data modeling and data warehouse architecture.
  • Ability to translate complex business requirements into scalable data models.
  • Ability to clearly communicate complex concepts with stakeholders.
  • Experience with cloud and data infrastructure (e.g., Snowflake, AWS, Redis).
  • Familiarity with DevOps frameworks and tools (e.g., Git, CI/CD).
  • Knowledge of containerization (e.g., Docker) and/or experience with Kubernetes is a plus.

Benefits & conditions

Comprehensive health insurance Professional development budget Flexible benefits package Hybrid work and generous leave options Free meals and snacks in-office Company-funded sport activities and team-building events, * Design, develop, and optimize data pipelines that ingest, process, and deliver reliable data.

  • Implement monitoring, governance, and best practices for data quality and security.
  • Partner with Analysts, ML Scientists, and Engineers to deliver structured datasets.
  • Manage and improve our data warehouse and infrastructure for analytics and ML use cases.
  • Experiment with advanced data modelling and analytical techniques.

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