Senior Data Architect (Azure + Databricks)

Description

Our client is a rapidly growing, automation-led service provider specializing in IT, business process outsourcing (BPO), and consulting services. With a strong focus on digital transformation, cloud solutions, and AI-driven automation, they help businesses optimize operations and enhance customer experiences. Backed by a global workforce of over 32,000 employees, our client fosters a culture of innovation, collaboration, and continuous learning, making it an exciting environment for professionals looking to advance their careers.

Committed to excellence, our client serves 31 Fortune 500 companies across industries such as financial services, healthcare, and manufacturing. Their approach is driven by the Automate Everything, Cloudify Everything, and Transform Customer Experiences strategy, ensuring they stay ahead in an evolving digital landscape.

As a company that values growth and professional development, our client offers global career opportunities, a dynamic work environment, and exposure to high-impact projects. With 54 offices worldwide and a presence in 39 delivery centers across 28 countries, employees benefit from an international network of expertise and innovation. Their commitment to a 'customer success, first and always' philosophy ensures a rewarding and forward-thinking workplace for driven professionals.

We are currently searching for a Senior Data Architect (Azure + Databricks):

Responsibilities:

• Lead target architecture design for Lakehouse/Warehouse environments using Azure ADLS Gen2, Databricks (Spark/Delta), Synapse/Fabric, and ADF.
• Define ingestion patterns (batch/streaming), transformation (ELT/ETL), and consumption layers (Bronze, Silver, and Gold).
• Optimize platform reliability and costs through cluster sizing, partitioning, and workload orchestration.
• Direct data modeling at conceptual, logical, and physical levels (OLTP/OLAP) and dimensional design (Star/Snowflake).
• Establish engineering standards for code quality, testing, CI/CD, and observability for pipelines and notebooks.
• Implement Data Governance using Microsoft Purview (catalog, lineage, classifications, and RBAC/ABAC).
• Oversee technical security and compliance across the entire data platform.
• Provide technical leadership through code reviews (SQL, Python), mentoring data engineers, and translating business needs into scalable roadmaps.

Requirements:

• 8 to 15 years of total experience, with at least 5 years specializing in Data Architecture for analytical platforms.
• Advanced expertise in the Azure ecosystem: ADLS Gen2, Databricks (Spark/Delta), Synapse/Fabric, and Azure Data Factory.
• Expert command of SQL and Python applied to data engineering and Spark performance optimization.
• Proven track record in data modeling (dimensional, star, normalization).
• Solid knowledge of Data Governance, preferably with Microsoft Purview (catalog and policies).
• Deep understanding of distributed systems (partitioning, scalability, and fault tolerance).
• Technical leadership skills to establish standards, provide mentorship, and communicate effectively with stakeholders.

Desired:

• Experience with Streaming technologies (Kafka, Azure Event Hubs) and CDC patterns.
• Alignment with Power BI for data models and semantic layers.
• Familiarity with Snowflake or knowledge of other clouds (AWS/GCP).
• Exposure to tools like Collibra or ML pipelines.

Languages

• Advanced Oral English.
• Native Spanish.

Note:

• Fully remote.

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Requirements

Requirements:

• 8 to 15 years of total experience, with at least 5 years specializing in Data Architecture for analytical platforms.
• Advanced expertise in the Azure ecosystem: ADLS Gen2, Databricks (Spark/Delta), Synapse/Fabric, and Azure Data Factory.
• Expert command of SQL and Python applied to data engineering and Spark performance optimization.
• Proven track record in data modeling (dimensional, star, normalization).
• Solid knowledge of Data Governance, preferably with Microsoft Purview (catalog and policies).
• Deep understanding of distributed systems (partitioning, scalability, and fault tolerance).
• Technical leadership skills to establish standards, provide mentorship, and communicate effectively with stakeholders.