Data Architect (Databricks)

As a Data Architect, you will be at the forefront of designing and architecting comprehensive data solutions across multiple platforms aligned with client needs and objectives.

Role & Responsibilities:

• Lead data architecture transformations and/or migration to modern cloud solutions, ensuring robustness and scalability of the soltuion.
• Design and implement Virtual Cloud solutions including virtual network and management of network routings and subnets.
• Design efficient, scalable ETL/ELT pipelines that streamline data processing and integration. Experience with integrating data across disparate systems using APIs and data integration tools
• Design scalable, high-performance data models and databases, including Medallion Data Warehouse architecture, Data Lakehouses, dimensión modelling (Star and/or Snowflake schemas), and other relevant design patterns.
• Manage one or more Data projects, owning the end-to-end execution and owning responsibilty of the outcomes
• Lead cross-functional teams to deliver on client goals, providing technical guidance and ensuring alignment with best practices.
• Engage with clients and stakeholders to understand business goals, provide technical expertise, and deliver tailored solutions.
• Ensure all designed solutions meet the highest standards of quality, performance cost-effectiveness, and access policy management.
• Stay updated with emerging industry trends and technologies, integrating them into solutions to provide added value to clients.

Hard Skills - Must have:

• Advanced or expert-level experience with Databricks, including Delta Lake, Lakehouse architecture, and data engineering workloads.
• Strong experience with SQL and data modeling, including Star and Snowflake schemas and dimensional modeling.
• Strong experience designing and implementing ETL/ELT pipelines and data integration solutions.
• Experience with Apache Spark / PySpark and large-scale data processing.
• Experience with at least one major cloud platform (AWS, Azure, or GCP) and cloud-based data solutions.
• Experience with data migration and modernization projects involving Databricks or other modern cloud data platforms.
• Experience with data integration and transformation tools such as dbt, Fivetran, Azure Data Factory, AWS Glue, Matillion, or similar.
• Familiarity with DataOps, CI/CD, infrastructure as code, and automation practices for data platforms.
• Familiarity with Agile/Scrum methodologies.

Soft Skills / Business Specific Skills:

• Strong technical leadership and ability to provide guidance to Data Engineers and other technical teams.
• Strong communication skills and ability to work effectively with clients, technical teams, and business stakeholders.
• Ability to translate business requirements into scalable and practical data architecture solutions.
• Experience working with distributed teams and clients.

Other Preferred Skills (Bonus points):

• Experience with Databricks Unity Catalog, Workflows, and governance capabilities.
• Experience with Databricks SQL and performance optimization.
• Experience with data governance, security, and access management.
• Experience with Power BI, Tableau, or other BI platforms.
• Experience with machine learning or ML workloads on Databricks.
• Experience with Terraform or other Infrastructure as Code tools.