Senior Data Engineer

Luxoft; Quincy (MA); On-site; USD 140,000 - 190,000; Full time

Job summary

Luxoft is modernizing and maintaining an eCommerce platform for a large US-based retailer, serving millions of omnichannel customers weekly. You will design scalable data pipelines, integrate with existing Azure-based architecture, and mentor engineers across cross-functional teams.

We seek an 8+ year senior Data Engineer with Azure Data Factory, Synapse, Databricks, and strong data modeling skills to drive migration, governance, and cloud-native analytics.

Qualifications

• 8+ years of overall experience with at least 1+ year in a Lead/Architect role.
• Hands-on Azure Data Factory and Synapse experience (3+ years).
• Designing data models from conceptual to physical to support storage and retrieval.
• Strong knowledge of Microsoft Azure services: ADLS, Synapse Analytics, Data Factory, Databricks with pySpark.
• Extensive experience building robust ETL/ELT pipelines to data lakes or data warehouses.
• Ability to integrate data from databases, APIs and external providers.
• Proficiency in dimensional modeling, star schemas, Data Mesh/Delta Lakehouse/Data Vault.
• SQL expertise for complex queries and performance tuning on cloud storages.
• Experience with metadata and governance in cloud platforms.
• Azure/Databricks certifications are a plus; knowledge of cloud analytical DBs.
• Experience with Azure MI, Azure Postgres, Cosmos DB, Analysis Services, and Informix.
• Python and Python-based ETL tools; Bash/Unix or Windows shell scripting.

Responsibilities

• We are looking for a Data Engineer who will design a solution for a big retail company; focus on processing big data and integrating with current architecture.

Skills

Azure Data Factory

Azure Synapse Analytics

Azure Data Lake Storage

Azure Databricks

Python

SQL

ETL Pipelines

Data Modeling

Data Warehousing

Shell Scripting

Leadership

Communication

Tools

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 a 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 the solution to current architecture.

SKILLS

• Readiness to work until 8.00 pm CET (no overtime required)
• Overall years of experience required 8+ (at least 1+ year in a Lead/Architect position)
• Strong, recent hands‑on expertise with Azure Data Factory and Synapse is a must (3+ years).
• 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.
• Demonstrated ability to lead cross‑functional engineering teams, define technical strategy and architecture, drive delivery of complex data platforms, mentor engineers, and effectively communicate with stakeholders at all organizational levels.

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.
• Ability to plan, estimate and track progress of implementing features
• Computer Science and data science academic and education credentials