Senior Data Consultant

Posted 2 months agoViewed

💎 Seniority level: Senior, Minimum 5 years

📍 Location: France

🔍 Industry: Data

🗣️ Languages: English

⏳ Experience: Minimum 5 years

🪄 Skills: PythonSQLETLGCPStrategyData StructuresNosql

Minimum 5 years of experience in a Senior Data position.
Proficiency in data analysis tools such as SQL and Python.
Familiarity with Google Cloud Platform (GCP) and BigQuery for data warehousing.
Experience in setting up ELT pipelines from scratch.
Good written and spoken English skills.
Strong attention to detail.
Optional: Experience building ELT pipelines for NoSQL databases (e.g., Firestore).

Posted about 2 months ago

📍 South Africa

🧭 Full-Time

🔍 IT leadership, cyber security, cloud solutions, and business intelligence

8-10 years of experience in data engineering or a related role with a strong background in building and optimizing data pipelines.
Expertise in PySpark for large-scale data processing and distributed computing.
Strong experience with Azure data technologies (Azure Data Factory, Azure Databricks, Azure SQL Database, etc.).
Proficiency in SQL and experience working with relational and NoSQL databases.
Experience with cloud-based data platforms and services, especially in Azure.
Solid understanding of ETL processes and data modeling techniques.
Strong problem-solving and troubleshooting skills.
Experience working with version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) practices.
Strong communication skills and the ability to work effectively within a collaborative, small-team environment.
A proactive, self-starter attitude with a passion for data engineering and technology.

Design, build, and maintain scalable data pipelines for the collection, transformation, and storage of data.
Work with large, complex datasets to ensure efficient processing and integration.
Develop data engineering solutions using Azure technologies and PySpark for distributed data processing.
Implement ETL processes and automate data workflows to support analytics, reporting, and business intelligence initiatives.
Collaborate with data scientists, business analysts, and stakeholders to understand data requirements and deliver actionable insights.
Ensure data quality, consistency, and reliability across all pipelines and datasets.
Optimize data models, storage, and processing workflows for performance and scalability.
Contribute to the architecture and design decisions for cloud-based data platforms.
Mentor junior team members and foster a collaborative and innovative team culture.
Troubleshoot and resolve issues related to data pipelines, ensuring high availability and performance.

DockerSQLAgileBusiness IntelligenceETLGitHadoopKafkaKubernetesSnowflakeAzureData engineeringNosqlSparkCommunication SkillsCI/CDTerraform

Posted about 2 months ago

🔧 Requirements