Big Data Architect (Azure)

About The Role In this role, you will design and deliver end-to-end data architectures on Azure for enterprise-scale data platforms and translate business needs into scalable, secure, and high-performance data solutions.

Responsibilities

• Lead architecture design and decision-making, defining standards, patterns, and best practices
• Collaborate with stakeholders to drive requirements gathering, data modeling, and solution design
• Support and guide engineering teams in implementing data pipelines and platform components
• Contribute to pre-sales activities, including workshops, solution envisioning, and proposal creation
• Build and evolve data platforms, including ingestion, transformation, storage, and serving layers
• Ensure data governance, quality, and security standards across the platform
• Participate in the full project lifecycle, from PoC through MVP to full-scale implementation
• Explore new technologies, build prototypes, and contribute to the Big Data community

Requirements

• Hands-on expertise in building large-scale data platforms, migrations, and decision-support systems
• Knowledge of designing and implementing modern data architectures (DWH, lakehouses, streaming, real-time, event-driven processing)
• Experience with Azure data ecosystem, including services such as Microsoft Fabric, Azure Synapse, Data Factory, ADLS Gen2, Cosmos, Azure SQL, Databricks, and Azure Stream Analytics
• Familiarity with SQL and Python (PySpark) for designing and optimizing data solutions
• Experience in translating business requirements into scalable architecture and implementation roadmaps
• Openness for acting as a customer-facing consultant, presenting architecture decisions, and leading technical discussions
• Readiness for leading and mentoring data engineering teams, providing technical direction, and ensuring best practices
• Knowledge of data governance, security, and data management frameworks across modern data platforms
• Familiarity with streaming and real-time processing (e.g., Kafka, Event Hub, Spark Structured Streaming)
• Hands-on experience in SDLC and software engineering best practices (CI/CD, version control, testing) applied to data platforms
• Proficiency in supporting pre-sales activities, including discovery, solution shaping, and high-level estimations
• Working proficiency in English, with excellent communication and presentation skills in a multicultural environment

SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.