Data Architect

Role & responsibilities

• Architect and implement end-to-end data pipelines, data lakes, and warehouses using modern cloud services and architectural patterns.
• Develop and build analytics tools that deliver actionable insights to the business.
• Integrate and manage large, complex data sets to meet strategic business requirements.
• Optimize data processing workflows using frameworks such as PySpark.
• Establish and enforce best practices for data quality, integrity, security, and performance across the entire data ecosystem.
• Collaborate with cross-functional teams to prioritize deliverables and design solutions.
• Develop compelling business cases and return on investment (ROI) analyses to support strategic initiatives.
• Drive process improvements for enhanced data delivery speed and reliability.
• Provide technical leadership, training, and mentorship to team members, promoting a culture of excellence.

Preferred candidate profile

• 8 years in Business Intelligence (BI) solution design, with 6+ years specializing in ETL processes and data warehouse architecture.
• 6+ years of hands-on experience with Azure Data services including Azure Data Factory,

  Azure Databricks

  , Azure Data Lake Gen2, Azure SQL DB, Synapse,

  Power BI, and

  MS Fabric (Understanding)

• Strong Python and PySpark software engineering proficiency, coupled with a proven track record of building and optimizing big data pipelines, architectures, and datasets.
• Proficient in transforming, processing, and extracting insights from vast, disparate datasets, and building robust data pipelines for metadata, dependency, and workload management.
• Familiarity with software development lifecycles/methodologies, particularly Agile.

• Experience with SAP/ERP/Datasphere data modeling is a significant plus. (Added Advantage)

• Excellent presentation and collaboration skills, capable of creating formal documentation and supporting cross-functional teams in a dynamic environment.
• Strong problem-solving, time management, and organizational abilities.
• Keen to learn new languages and technologies continually.
• Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or an equivalent field.