Description

You will design and implement complex, large-scale data architectures and lead the full lifecycle of Spark solutions.

Responsibilities

• Design complex, high-performance data architectures and specify technical solutions based on scoped client requirements.
• Lead client engagements to develop application development strategies and act as a bridge between business and technical leadership.
• Mentor IT consultants and coordinate with developers, architects, and cross-functional stakeholder teams.
• Identify and resolve performance bottlenecks through application and database tuning.
• Translate end-user requirements into technical documentation and architectural position papers.

Required Skills

• 11–16 years of experience designing and implementing large-scale data processing applications.
• Hands-on expertise in Java, .NET, or Python.
• Extensive experience in data modeling and database design across data warehousing and BI systems.
• Proficiency in relational databases including Oracle, SQL Server, and PostgreSQL.
• Expertise in Azure Data Factory, ADLS Gen 2, Azure Databricks, PySpark, and Azure Synapse.
• Strong understanding of big data analytics platforms, ETL, and the full SDLC.
• Experience with NoSQL technologies such as Cassandra, MongoDB, HBase, or Azure-based NoSQL.
• Proven ability to manage Spark solution lifecycles within multi-technology environments.
• Strong engineering abilities to perform hands-on application and database performance tuning.

Preferred Skills

• Experience contributing to thought leadership through executive presentations and architecture documents.

Key Skills

Education

Any Graduate