Senior Data Solutions Engineer [Python / SQL / Databrick / ETL / Azure]

We are looking for a versatile Data Solutions Engineer capable of supporting the complete data lifecycle, from data ingestion and engineering to analytics, visualization, and API enablement.The ideal candidate combines strong Data Engineering fundamentals with the ability to work closely with business stakeholders, develop reporting solutions, and contribute across multiple data-related initiatives. Exposure to Data Science and AI use cases is considered an advantage.This role requires a flexible mindset, as the engineer may rotate between Data Engineering, Data Analytics, and Data Visualization initiatives depending on project priorities.

Responsibilities

• Design, develop, and maintain scalable data pipelines.

• Build and optimize ETL/ELT processes.

• Develop data ingestion, transformation, and aggregation workflows.

• Ensure data quality, reliability, and performance.

• Develop solutions using cloud-based data platforms.

• Build and optimize data processing notebooks and workflows.

• Work with Data Lakes, Lakehouse architectures, and distributed data processing technologies.

• Support CI/CD and deployment activities for data solutions.

• Collaborate with business users to gather and clarify requirements.

• Translate business needs into analytical and technical solutions.

• Develop KPI calculations, reporting logic, and support data exploration for business insights.

• Build dashboards and reports to enable self-service analytics and decision-making.

• Develop and maintain APIs to expose data products and integrate with consuming applications.

Required Skills

Programming:

• Python

• SQL

• Databricks or Apache Spark / PySpark

• Examples:

• Synapse Analytics

• Microsoft Fabric

Data Processing:

• ETL / ELT

• Data Modeling

APIs:

• FastAPI (preferred)

• Flask / REST API development experience acceptable