Location
Remote (United States)
Seniority
Senior · 7+ years exp
Employment
Full-Time
Removed from the employer's board on Nov 6, 2026. First seen by Alion on Oct 3, 2026. Luxoft scores A on the Alion truth index.
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Luxoft is a software engineering and IT consulting company founded in 2000 and owned by DXC Technology since 2019. Headquartered in Zug, Switzerland, it builds custom software, testing and cloud solutions for clients in automotive, financial services, healthcare, media and telecommunications. Its delivery centers in countries such as Romania, Poland, India and Serbia hire QA engineers, DevOps engineers, backend developers and data engineers.
Project description
Join Our Team: Innovating Health Care with Cutting-Edge Technology
Responsibilities
Primary Responsibilities:
Design and develop ETL/ELT solutions on Azure Databricks, LakeBase and Spark
Develop, implement, and deploy large scale data pipelines empowering machine learning algorithms, insights generation, business intelligence dashboards, reporting and new data products
Design, build, optimize, and manage modern large-scale data pipelines ETL/ELT processing to support data integration for analytics, machine learning features and predictive modelling
Consume data from a variety of sources (RDBMS, APIs, FTPs and other cloud storage) & formats (Excel, CSV, XML, JSON, Parquet, Unstructured)
Write advanced / complex SQL with performance tuning and optimization
Build AI based solutions for solving business needs, process automations and improving operational efficiency
Identify ways to improve data reliability, data integrity, system efficiency and quality
Participate in architectural evolution of data engineering patterns, frameworks, systems, and platforms including defining best practices and standards for managing data collections and integration
Mentor other data engineers and provide technical direction by teaching other data engineers how to leverage cloud data platforms
Skills
Must have
Required Qualifications:
7 + years of experience in data engineering, data integration, data modeling, data architecture, and ETL/ELT processes to provide quality data and analytics solutions
5 + years of experience in Python
3+ Experience with API design and lifecycle management (GraphQL, REST, etc.)
2 + years Hands-on experience with Redis-backed state management and event-driven processing.
2 + years of experience in Apache Spark (PySpark/Spark SQL)
2+ years building and deploying Cloud based solutions using
Azure Databricks with UC, Snowflake, Functions, Service Bus
2+ years of experience in SQL with designing complex data schemas and query performance optimization
Experience building LLM integrations for workflow automation/business needs.
Experience with DevOps automation with Terraform.
Experience with CI/CD process and tools - GitHub Actions, GIT, Artifactory, Sonar
Preferred Qualifications:
Bachelor's degree in Computer Science, Engineering, Mathematics or related discipline
Extensive knowledge of data architecture principles (e.g., Data Lake, Databricks Delta Lake, Data Warehousing, etc.)
Extensive knowledge of data modelling techniques including slowly changing dimensions, aggregation, partitioning and indexing strategies
Experience working with LLMs
Ability to independently troubleshoot and performance tune large scale enterprise systems
Excellent collaborator with experience working effectively with cross-functional teams such as leadership, product management and engineering, with a willingness to inspire other data engineers, data scientists and analysts
Solid communication skills with the ability to communicate technical concepts to both technical and non-technical audiences
Nice to have
Exceptional communication skills.
Ability to deliver exceptional customer service with a positive attitude.
Other
Languages
English: C1 Advanced
Seniority
Senior
Join Our Team: Innovating Health Care with Cutting-Edge Technology
Responsibilities
Primary Responsibilities:
Design and develop ETL/ELT solutions on Azure Databricks, LakeBase and Spark
Develop, implement, and deploy large scale data pipelines empowering machine learning algorithms, insights generation, business intelligence dashboards, reporting and new data products
Design, build, optimize, and manage modern large-scale data pipelines ETL/ELT processing to support data integration for analytics, machine learning features and predictive modelling
Consume data from a variety of sources (RDBMS, APIs, FTPs and other cloud storage) & formats (Excel, CSV, XML, JSON, Parquet, Unstructured)
Write advanced / complex SQL with performance tuning and optimization
Build AI based solutions for solving business needs, process automations and improving operational efficiency
Identify ways to improve data reliability, data integrity, system efficiency and quality
Participate in architectural evolution of data engineering patterns, frameworks, systems, and platforms including defining best practices and standards for managing data collections and integration
Mentor other data engineers and provide technical direction by teaching other data engineers how to leverage cloud data platforms
Skills
Must have
Required Qualifications:
7 + years of experience in data engineering, data integration, data modeling, data architecture, and ETL/ELT processes to provide quality data and analytics solutions
5 + years of experience in Python
3+ Experience with API design and lifecycle management (GraphQL, REST, etc.)
2 + years Hands-on experience with Redis-backed state management and event-driven processing.
2 + years of experience in Apache Spark (PySpark/Spark SQL)
2+ years building and deploying Cloud based solutions using
Azure Databricks with UC, Snowflake, Functions, Service Bus
2+ years of experience in SQL with designing complex data schemas and query performance optimization
Experience building LLM integrations for workflow automation/business needs.
Experience with DevOps automation with Terraform.
Experience with CI/CD process and tools - GitHub Actions, GIT, Artifactory, Sonar
Preferred Qualifications:
Bachelor's degree in Computer Science, Engineering, Mathematics or related discipline
Extensive knowledge of data architecture principles (e.g., Data Lake, Databricks Delta Lake, Data Warehousing, etc.)
Extensive knowledge of data modelling techniques including slowly changing dimensions, aggregation, partitioning and indexing strategies
Experience working with LLMs
Ability to independently troubleshoot and performance tune large scale enterprise systems
Excellent collaborator with experience working effectively with cross-functional teams such as leadership, product management and engineering, with a willingness to inspire other data engineers, data scientists and analysts
Solid communication skills with the ability to communicate technical concepts to both technical and non-technical audiences
Nice to have
Exceptional communication skills.
Ability to deliver exceptional customer service with a positive attitude.
Other
Languages
English: C1 Advanced
Seniority
Senior
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