Senior Data Science Developers

Must Haves Azure Databricks Python,Azure Data Factory , Power BI Description Data Science Developer – Deliverables The candidates will perform Data Science Developer work by creating, enhancing, maintaining, supporting, and sustaining existing pipelines, analytics models, and data products Specific Deliverables Deliverables Expected To Be Produced Could Include Creating, enhancing, maintaining, and supporting structures for storage of data in formats that are suitable for consumption in analytics solutions. Automation of data pipelines used to ingest, prepare, transform, and model data for use in analytics products. Creating, enhancing, maintaining, and supporting dashboards and reports. Creating, enhancing, maintaining, and supporting analytics environments and implementing new technology to improve performance, simplify architecture patterns, and reduce cloud hosting costs. Knowledge transfer sessions and documentation for technical staff related to architecting, designing, and implementing continuous improvement enhancements to analytics solutions. These sessions will be held as needed and on a case by case basis that involve walkthroughs of documentation, code, and environment setups. Skills Experience and Skill Set Requirements Data Science Developer – Evaluation Criteria Data Storage and Preparation – 35% The candidate must demonstrate their experience with Azure Storage, Azure Data Lake, Azure Databricks Lakehouse, and Azure Synapse structures in real world implementations Data Pipelines – 35% The candidate must demonstrate their experience with automating data pipelines using appropriate Microsoft Azure Platform/Technologies (SQL,Python, Databricks and Azure Data Factory) Data Analytics – 15% The candidate must demonstrate their experience with Power BI reports and dashboards Knowledge Transfer – 15% The candidate must demonstrate experience in conducting knowledge transfer sessions and building documentation for technical staff related to architecting, designing, and implementing end to end analytics solutions Hybrid:3 days per week in the office

The candidate will create, maintain, and support data pipelines, analytics models, and data products to ensure efficient data storage and consumption. They are also responsible for developing dashboards, automating ingestion processes, and conducting knowledge transfer sessions for technical staff.

Applicants must have extensive experience with the Microsoft Azure platform, specifically Databricks, Data Factory, and Synapse. Proficiency in Python, SQL, and Power BI is required to manage end-to-end analytics solutions.

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Azure Databricks
• Python
• Azure Data Factory
• Power BI
• Azure Storage
• Azure Data Lake
• Azure Databricks Lakehouse
• Azure Synapse
• SQL
• Data Pipeline Automation
• Data Modeling
• Dashboard Development
• Technical Documentation
• Knowledge Transfer

• Data & Analytics
• Technology
• Software
• Consulting

Expérience minimale

5+ ans

Postuler avant le

20 août 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Présence au bureau

3 jours par semaine

Niveau d’expérience

Mid-Senior level