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SoftServe
Open role>1 month

Big Data Architect (Azure)

SoftServeUkraine
Work model
Hybrid
Experience
7+ years
Employment
Full Time
Compensation
Not disclosed
Technology signal
8 tags

Technology context

8

Parsed from the vacancy text; ordered by relevance to this role.

AzurePythonKafkaScalabilitySparkDatabricksCI/CDSQL

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Role description

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

  • Proven experience as a BigData Architect 2+ years
  • 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