Data Engineer

Publicis Global Delivery (PGD); Bogotá, Distrito Capital; Presencial; COP 153.356.592 - 230.034.888; Jornada completa

Descripción de la vacante

A global marketing services firm in Bogotá seeks a Data Engineer to lead data management projects. Responsibilities include developing data pipelines, optimizing data models, and collaborating with cross-functional teams to ensure data quality and availability. Candidates should possess a Bachelor’s degree and over 3 years of experience in Data Engineering, with strong skills in Python, SQL, and familiarity with Big Data frameworks. This full-time role offers an opportunity to contribute to impactful projects in a dynamic environment.

Formación

• 3+ years of experience in Data Engineering or Data Science with large-scale projects.
• Strong proficiency in Python and SQL.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of Big Data frameworks such as Databricks, Spark, or Hadoop.
• Experience with data transformation and orchestration tools (dbt, Airflow, ADF, etc.).
• Intermediate to advanced English for technical communication.

Responsabilidades

• Design, develop, and maintain robust data pipelines (ETL/ELT).
• Build and optimize data models for analysis.
• Develop and optimize SQL queries and Python scripts.
• Implement and monitor data validation, quality checks, and performance.

Conocimientos

Python

SQL

Data management

Data transformation

Big Data frameworks

Cloud platforms

Data visualization

Statistical analysis

Educación

Bachelor’s degree in Computer Science, Mathematics, Engineering, or related field

Herramientas

Databricks

Spark

Hadoop

AWS

Azure

GCP

dbt

Airflow

ADF

Tableau

Looker Studio

Descripción del empleo

Data Engineer – Publicis Global Delivery (PGD)

We are looking for professionals in Data Engineering to join our team and lead high-impact projects in data management, integration, and analytics. The role involves designing, building, and maintaining scalable data solutions that support strategic decision-making in Big Data and Cloud environments, while ensuring data quality, integrity, and availability. You will collaborate closely with cross-functional teams, bringing technical expertise to transform complex datasets into actionable insights.

Responsibilities

• Design, develop, and maintain robust data pipelines (ETL/ELT) to integrate and transform data from diverse sources
• Build and optimize data models for analysis, ensuring governance and data quality
• Develop and optimize SQL queries and Python scripts for large-scale data processing
• Leverage technologies such as Databricks, Spark, Hadoop, BigQuery, or similar for big data processing
• Implement and monitor data validation, quality checks, and pipeline performance
• Collaborate with data analysts, data scientists, and business stakeholders to translate requirements into technical solutions
• Apply engineering best practices: version control (Git), documentation, testing, and CI/CD
• In senior roles: mentor team members, set technical standards, and act as a reference point for best practices

Qualifications

• Bachelor’s degree in Computer Science, Mathematics, Engineering, or related field
• 3+ years of experience in Data Engineering or Data Science with large-scale projects
• Strong proficiency in Python and SQL
• Hands‑on experience with cloud platforms (AWS, Azure, or GCP)
• Knowledge of Big Data frameworks such as Databricks, Spark, or Hadoop
• Experience with data transformation and orchestration tools (dbt, Airflow, ADF, etc.)
• Familiarity with data visualization tools (Tableau, Looker Studio)
• Background in statistical analysis (time series, audience modeling) is a plus
• Intermediate to advanced English, with the ability to communicate technical concepts to different audiences
• (Nice to have) Experience in digital media or marketing analytics

Seniority Level

Mid‑Senior level

Employment Type

Full‑time

Job Function

Accounting/Auditing, Consulting, and Information Technology

Industries

Marketing Services and Data Infrastructure and Analytics>