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 one or more Database technologies (e.g. SQL Server) and modern data warehousing solutions (e.g., Snowflake, Databricks, Redshift, BigQuery).
- Experience with integrating data across disparate systems using APIs and data integration toolsProficiency in industry leading data movement and transformation tolos such as Snaplogic, dbt, Matillion, Fivetran, Azure Data Factory, AWS Glue
- Expertise in advanced analytics, including predictive modeling and statistical analysis.
- Experience with BI tools (e.g., Tableau, Power BI, Looker) for data visualization and data análisis tolos (e.g. Python, R) for decision-making.
- Familiarity with DevOps practices for data (e.g., DataOps) and automation tools (e.g., Jenkins, Terraform) to streamline data workflows.
- Familiarity with Agile/Scrum methodologies.
Soft Skills / Business Specific Skills:- Strong leadership skills with experience managing data teams, including data engineers and analysts
- Sociable and able to build positive relationships across all levels of an organization.
- Ability to communicate effectively with clients, leadership, and executive teams.
- Experience working with distributed teams and clients.
Other Preferred Skills (Bonus points):- Understanding of data governance frameworks and best practices.
- Experience building and deploying ML models using ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
- Familiarity with cloud-based AI/ML platforms (e.g., AWS SageMaker, Google AI Platform, Azure ML).
- Experience with Generative AI models and applications, and understanding of ethical implications and bias mitigation strategies in Generative AI.
