• Translate business requirements into technical specifications, data models, data streams, and databases • Convert or embed ML/AI workflows into production-grade, enterprise systems • Design, develop, and maintain infrastructure for geospatial analysis and ML/AI applications on large data • Develop API-driven backend services with FastAPI, Pydantic, and async Python • Work with columnar analytics stacks (DuckDB, PyArrow, Parquet / GeoParquet) • Deploy monitoring tools to track status and performance of system architecture and data flows • Propose enterprise data architecture solutions in support of business development.

• odpowiedzialność za całość rozwiązań współtworzonych wraz z zespołem, • tworzenie lub modyfikowanie rozwiązań do przetwarzania danych w chmurze, • tworzenie i modyfikowanie dokumentacji, • analizowanie i optymalizowanie rozwiązań w zakresie działającego lub projektowanego systemu, • analizowanie wymagań klienta pod kątem dostarczenia optymalnego rozwiązania jego potrzeby biznesowej, • analizowanie potencjalnych zagrożeń, • dostosowywanie rozwiązań względem wymagań biznesowych.

• Reporting to a Technical Lead, this role plays a critical part in supporting the Data Ingestion team and both Business and Technical Product Owners. • Contribute to the expansion and adoption of data products across multiple service lines, products, functions, and delivery teams. • Collaborate with stakeholders to identify and ideate opportunities for continuous improvement of data assets and the services provided to data consumers. • Participate in design and development sessions to enhance data asset creation and ingestion pipelines, with a strong focus on stability, performance optimization, and traceability. • Design, develop, test, and maintain data ingestion pipelines and supporting processes. • Build resilient, fault-tolerant, and modular code to ensure data pipelines and services are robust, scalable, and highly available. • Research, evaluate, and implement new tools, methods, and processes to enable the creation of high-quality, enterprise-grade data products and services. • Actively collaborate across teams to ensure seamless transitions between data ingestion, consumption, and activation stages. • Contribute to documentation, reporting, and knowledge sharing to support long-term platform sustainability.

• Design, build, and maintain scalable ETL/ELT pipelines to ingest data from multiple sources including advertising platforms (Google Ads, Facebook Ads, Bing Ads), CRM systems, and operational databases • Manage and optimize our Snowflake data warehouse, including schema design, query performance tuning, and cost optimization • Configure and maintain Fivetran connectors and data integrations, ensuring data quality and timely syncs across all platforms • Develop and maintain data transformation layers using SQL and dbt to create clean, reliable datasets for analytics consumption • Build and manage automated workflows and Snowflake tasks for scheduled data refreshes and reporting • Partner with the analytics team to understand data requirements and translate them into robust technical solutions • Implement data quality monitoring, alerting, and validation frameworks to ensure accuracy and completeness • Document data models, pipelines, and processes to maintain institutional knowledge • Support HIPAA-compliant data handling practices and maintain appropriate access controls • Troubleshoot data issues and perform root cause analysis when discrepancies arise