• Collaborate and partner with stakeholders, and decision-makers to prioritize, design, and fulfill their data analytics needs. • Identify KPIs driving business growth and performance and work closely with the business teams to define them. • Work across the data stack to design and build various data products (pipelines, data models, analysis) that enable the business to make data backed decisions. • Help garner trust in data from the business by documenting analytics best practices, assisting with data discoverability, governance, and accuracy. • Promote and drive a self-service data culture by building easy to use analytics products and teaching the technical and non-technical users how to use them. • Communicate progress, risks, and completion of projects to stakeholders.

• Design, build and evolve the company’s data platform architecture. • Develop and maintain ETL/ELT pipelines, including API extraction, transformations, incremental loads and CDC (Change Data Capture). • Model data for Data Warehouse, Data Lake and Data Marts, applying dimensional modeling (Star Schema, Snowflake Schema). • Implement batch and streaming processing with event-driven architecture and asynchronous processing. • Ensure database performance and reliability: relational modeling, indexes, partitioning, query optimization and replication. • Establish Data Quality, Data Lineage, Data Catalog and Data Governance practices. • Orchestrate pipelines and handle historical data with versioning and traceability. • Implement pipeline observability: logs, metrics, monitoring and alerts. • Provide reliable and near real-time data for dashboards, operational analytics and business intelligence. • Prepare the data foundation for future Machine Learning initiatives. • Automate processes and deployments using GitHub Actions and Docker. • Collaborate with product, engineering and business teams to define requirements and KPIs.

• Design, develop and maintain scalable data pipelines to ingest, process and transform large volumes of structured and unstructured data from diverse sources. • Implement efficient processes to ensure accurate and timely delivery of data to downstream systems and applications. • Ensure data quality, security and governance across the entire pipeline.

• Collaborate with Product Managers, Business Analysts, DevOps teams, Engineering teams, PMO. • Deliver scalable enterprise cloud solutions. • Provide architectural options and technical recommendations. • Conduct cost-benefit analysis and risk assessments. • Lead the modernization of data platforms, ETL pipelines, and analytics ecosystems.