Senior Data Engineer

Luxoft; United Kingdom; Remote; GBP 60,000 - 80,000; Full time

Job summary

A global technology company is seeking a Data Engineer to design solutions for a significant eCommerce platform. The role focuses on supporting big data processes and integrating solutions into existing architecture. The ideal candidate should have strong expertise in Azure Data Factory and Synapse, with experience in leading teams and creating ETL/ELT pipelines. This position offers the opportunity to work on high-impact data projects in a dynamic environment.

Qualifications

• Strong expertise in Azure Data Factory and Synapse (3+ years).
• Experience in leading a distributed team.
• Proficiency in SQL for complex queries and performance tuning.

Responsibilities

• Design a solution to support processing of big data volumes.
• Integrate data solutions with current architecture.
• Build robust and scalable ETL/ELT pipelines.

Skills

Azure Data Factory

Data modeling

ETL/ELT pipelines

SQL

Azure Synapse Analytics

Python

Azure Data Lake Storage

Data governance

Tools

Azure Databricks

Docker

Kubernetes

Job description

Project description

The primary goal of the project is the modernization, maintenance and development of an eCommerce platform for a big US-based retail company, serving millions of omnichannel customers each week.Solutions are delivered by several Product Teams focused on different domains - Customer, Loyalty, Search and Browse, Data Integration, Cart.Current overriding priorities are new brands onboarding, re-architecture, database migrations, migration of microservices to a unified cloud-native solution without any disruption to business.

Responsibilities

• We are looking for Data Engineer who will be responsible for designing a solution for a big retail company. The main focus is to support processing of big data volumes and integrate solution to current architecture.

SKILLS

Must have

• Strong, recent hands-on expertise with Azure Data Factory and Synapse is a must (3+ years).
• Experience in leading a distributed team.
• Strong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval.
• Strong knowledge of Microsoft Azure, including Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, and Azure Databricks, pySpark for building scalable and reliable data solutions.
• Extensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses.
• Ability to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing.
• Proficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault)
• Proficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages.
• Experience integrating metadata and governance processes into cloud-based data platforms
• Certification in Azure, Databricks, or other relevant technologies is an added advantage
• Experience with cloud-based analytical databases.
• Experience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix.
• Experience with Python and Python-based ETL tools.
• Experience with shell scripting in Bash, Unix or windows shell is preferable.

Nice to have

• Experience with Elasticsearch• Familiarity with containerization and orchestration technologies (Docker, Kubernetes).• Troubleshooting and Performance Tuning: Ability to identify and resolve performance bottlenecks in data processing workflows and optimize data pipelines for efficient data ingestion and analysis.• Collaboration and Communication: Strong interpersonal skills to collaborate effectively with stakeholders, data engineers, data scientists, and other cross-functional teams.