Data Architect (Databricks)

Allata is a global consulting and technology services firm founded in 2016, with 350+ employees across the US, India, and Argentina. We partner with some of the world's largest enterprises to move AI from idea to production — building intelligent agents, data foundations, and governance frameworks that scale.

Our teams work at the intersection of strategy, engineering, data, and design, helping clients modernize their technology, unlock data value, and create meaningful digital experiences. At Allata, you'll join an agile, cross-functional team that works closely alongside clients — making a real impact and building lasting partnerships.

• 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.

• 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.

• 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.

• 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.

Originally posted on Himalayas