Addepto

Data Engineer

• Lead data architecture and engineering projects within GCP and Snowflake environments, including migration, transformation, and platform design.
• Design end-to-end data architectures (ingestion, storage, processing, and serving layers).
• Define and guide implementation of data integration, ETL/ELT strategies, and pipeline architectures.
• Develop logical and physical data models, schemas, and data structures across business domains.
• Guide clients on data strategy, architecture decisions, and best practices across GCP.
• Design and enforce data governance, security, and access control frameworks.
• Work closely with security teams to ensure data protection and compliance.
• Lead client workshops to identify data sources, flows, and requirements.
• Define future-state architectures, roadmaps, and implementation plans.
• Collaborate with cross-functional teams (data scientists, engineers, business stakeholders) to deliver data solutions.
• Evaluate and select tools, frameworks, and architectural patterns.
• Provide technical leadership and mentorship to engineering teams.
• Oversee performance optimization, scalability, and cost efficiency of data platforms.

Data Architect, GCP, Snowflake

• Design, develop, test, and maintain data pipelines and ETL/ELT processes using GCP and Snowflake.
• Implement data ingestion, transformation, and storage solutions for structured, semi-structured, and unstructured data.
• Build and optimize batch, micro-batch, and real-time data pipelines.
• Support data migration from legacy systems to cloud platforms (GCP, Snowflake).
• Collaborate with business and technical stakeholders to translate requirements into scalable data solutions.
• Work with GCP services such as BigQuery, Cloud SQL, Cloud Spanner, and Cloud Bigtable.
• Integrate data from various sources and support data platform development.
• Ensure data quality by implementing validation rules, testing frameworks, and monitoring solutions.
• Work closely with security teams to ensure data protection, access control, and compliance.
• Support development of data models and schemas for analytics and reporting.
• Contribute to CI/CD processes, version control, and infrastructure automation (e.g., Git, Terraform).
• Collaborate with data scientists, analysts, and engineers to support data-driven use cases.

Data Engineer, GCP, Snowflake

Pre-sales Engineer

• Serve as a technical advisor during pre-sales and early engagement stages, helping clients understand what’s possible with AI/LLMs and modern data platforms, and how these capabilities align with their strategic business goals.
• Lead or support technical discovery sessions, clarifying business problems, identifying solution patterns, and assessing feasibility across both AI/ML and data platform initiatives.
• Design and communicate solution architectures, including LLM integrations, AI/ML solution designs, retrieval-augmented generation (RAG), vector databases, orchestration pipelines, and data flows, as well as modern cloud data architectures such as data lakes, data warehouses, and big data processing solutions.
• Create and deliver technical PoCs and PoVs, demo narratives, and early prototypes to support proposals and shape delivery, including solutions leveraging AI/ML as well as modern data engineering and analytics platforms.
• Collaborate with sales, delivery, and engineering teams to ensure a smooth transition from pre-sales, through technical scoping and solution design, to hand-off to delivery teams and full implementation.

Pre-Sales Engineer, AI & Big Data

Data Scientist

• Lead the development, implementation, and validation of Machine Learning solutions, ensuring alignment with project objectives.
• Lead the design of AI solution architectures that meet complex business goals and drive innovation.
• Research, test and select the best tools and technologies as well as AI solutions to meet the business requirements.
• Lead and mentor cross-functional teams, encouraging collaboration and helping everyone grow their skills.
• Understand clients' needs and translate business problems into data science problems.
• Architect and oversee the implementation of data pipelines and workflows, setting standards for data quality and security.
• Coordinate with Data Engineering and Software Engineering teams to strategize and oversee the building of AI applications.
• Present findings and recommendations clearly and concisely to stakeholders.
• Prioritize, and control tasks within an Agile/Scrum framework, ensuring timely delivery.

Data Architect, GCP, Snowflake

Data Engineer, GCP, Snowflake

Pre-Sales Engineer, AI & Big Data

Data Scientist / AI Engineer