Application Developers | Data engineers

Luxoft; United Kingdom; Remote; GBP 70,000 - 120,000; Full time

Job summary

Luxoft is seeking a senior data engineer to design and deliver large-scale ETL/ELT pipelines on Azure Databricks, enabling ML and BI workloads. You will work across data sources and formats to build reliable data products and dashboards.

You will mentor junior engineers, shape data architecture, and implement best practices for data integration and quality. The role demands strong SQL, Python, Spark, and API skills, and a collaborative, cross-functional approach.

Qualifications

• 7+ years of experience in data engineering and ETL/ELT to deliver quality analytics solutions.
• 5+ years Python development and API design experience (GraphQL, REST).
• 2+ years Redis-backed state management and event-driven processing.
• 2+ years Apache Spark (PySpark/Spark SQL) and cloud data platforms (Azure Databricks).
• 2+ years SQL with complex schemas and query optimization.
• Experience building LLM integrations and DevOps automation with Terraform.

Responsibilities

• Design and develop ETL/ELT solutions on Azure Databricks and Spark-based platforms for analytics and ML.
• Consume data from RDBMS, APIs, FTPs and various formats (Excel, CSV, JSON, Parquet) and ensure quality.
• Write advanced SQL and optimize queries for performance.
• Mentor data engineers and participate in architectural evolution.

Skills

Python

PySpark/Spark SQL

Azure Databricks

SQL

ETL/ELT design

APIs (GraphQL/REST)

Redis state management

Terraform

Education

Bachelor's degree in Computer Science or related field

Tools

Snowflake

GitHub Actions

Service Bus

Job description

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 SparkDevelop, implement, and deploy large scale data pipelines empowering machine learning algorithms, insights generation, business intelligence dashboards, reporting and new data productsDesign, build, optimize, and manage modern large-scale data pipelines ETL/ELT processing to support data integration for analytics, machine learning features and predictive modellingConsume 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 optimizationBuild AI based solutions for solving business needs, process automations and improving operational efficiencyIdentify ways to improve data reliability, data integrity, system efficiency and qualityParticipate in architectural evolution of data engineering patterns, frameworks, systems, and platforms including defining best practices and standards for managing data collections and integrationMentor 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 solutions5 + years of experience in Python3+ 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 Bus2+ years of experience in SQL with designing complex data schemas and query performance optimizationExperience 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, SonarPreferred Qualifications:Bachelor’s degree in Computer Science, Engineering, Mathematics or related disciplineExtensive 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 strategiesExperience working with LLMsAbility to independently troubleshoot and performance tune large scale enterprise systemsExcellent 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 analystsSolid 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.