Senior Data Solutions Engineer
Summary
Senior Data Solutions Engineer at Luxoft covering the full data lifecycle: building scalable cloud data pipelines on Azure (Databricks/Spark), ETL/ELT workflows, KPIs, dashboards, and APIs that expose data products. The role rotates across data engineering, analytics, and visualization based on project priorities.
Project description
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.
SKILLS
Must have
- Programming:- Python- SQLData Engineering:- Databricks or Apache Spark / PySparkCloud Platform:- Microsoft AzureExamples:Azure Databricks, Azure Data Factory, Azure Data Lake Storage, Azure, Synapse Analytics, Microsoft FabricData Processing:- ETL / ELT- Data Modeling- Data Pipeline DevelopmentAPIs:- FastAPI (preferred)- Flask / REST API development experience acceptableData VisualizationAt least one of:- Power BI- Tableau- Looker- Similar BI platform
Nice to have
Data Science & AIMachine Learning fundamentalsPredictive AnalyticsAI/ML model integrationStatistical analysisAdvanced Data PlatformAzure SynapseMicrosoft FabricAzure MLSnowflakeDevOpsAzure DevOpsGitCI/CD pipelines
Skills
- AI
- Analytics
- API
- Azure
- Azure Data Factory
- Azure Synapse
- CI/CD
- Cloud
- Data Analytics
- Data Engineering
- Data Ingestion
- Data Lake
- Data Modeling
- Data Pipelines
- Data Quality
- Data Science
- Data Visualization
- Databricks
- ELT
- ETL
- FastAPI
- Flask
- Lakehouse
- Looker
- Machine Learning
- Power BI
- Python
- REST
- Spark
- Tableau