Robert Serrat Morros

Software engineer maintaining the experimentation framework, enabling product teams to deliver new features and improvements via informed decisions.

• Enable new metrics to measure retention, user behaviour, and web vitals, coordinating and leading conversations with multiple teams (marketing, data, SRE, and product).
• Revamp the front-end application to improve usability, reduce confusion, and lessen the complexity of understanding experiment results and decision-making.
• Optimise the experimentation ETL to reduce infrastructure costs, and unblock teams.
• Enhancing existing tools to unblock product teams with new use cases.
• Collaborate and support product teams with their experiments.

Stack: Python, Django, GraphQL, React with Typescript, Redshift, Terraform, and AWS.

Software Engineer in the Openness team, responsible for integrating the main platform and pipeline with third-party tools such as Google Analytics, and Adobe Analytics.

• Led end-to-end execution of the Data Export project, enabling customers to extract data directly to their Data Warehouses, and pipelines. Managed all phases from conception, exploration, architecture proposal, roadmap definition, and PoC with final clients, to final implementation.
• Maintained and enhanced streaming data pipelines, integrating Google and Adobe Analytics into the solution. Executed incremental changes, handled production incidents, conducted bug fixing, and improved documentation and observability.

Stack: Scala, Golang, Kafka, DynamoDB, ClickHouse, Terraform, and AWS.

As part of the Data Platform team:

• Orchestrated the implementation of a streaming pipeline, leveraging Kafka and Kafka Streams with Scala, enabling real-time integrations and metrics computations.
• Led the optimisation of Sales and Marketing funnels and campaigns by integrating third-party tools (Salesforce, Iterable) into the Data Platform workflow.
• Designed and implemented data pipelines utilising Apache Airflow and Apache Spark, with Scala, for efficient data processing.
• Assumed responsibility for the ongoing maintenance of the Data Platform infrastructure.
• Development of data ingestion pipelines and integrations with Python.

Stack: Scala, Spark, Python, Kafka, Redshift, Glue, Athena, Terraform, Terragrunt, and AWS.

As part of the Data team:

• Developed and maintained the real-time operational backend to manage drivers' assignments, the back-office operators, and provide customers' real-time tracking.
• Integrated real-time operational backend data with back-office backend.

As part of the Data Platform team:

• Built ETL pipelines orchestrated through Airflow, executed with PySpark and Python Pandas, and modelled data to facilitate streamlined access for business analysts.

Stack: Scala, Akka, Kafka, Python, Airflow, Spark, and AWS.

Data engineer within the experimentation team (Houston team), specialising in the A/B testing platform, and delivering services to diverse teams across global marketplaces.

Focused on developing and optimising real-time data pipelines using Kafka Streams, and contributed to the scalability of the backend infrastructure with Scala Finatra.

• Designed and led the implementation of a multi-tenant streaming platform using Apache Kafka. Implemented the Confluent distribution on Kubernetes, incorporating components like Kafka Connect, Kafka Streams, Schema Registry, and REST Proxy. Also, developed a DB2 Kafka Connect connector for extracting data from mainframe systems.
• Contributed to the architecture, and provided support to development teams working on a Cloudera distribution platform, specifically the Oracle Big Data Appliance, for Apache Spark applications. Played a role in crafting solutions and delivering essential tools to enhance team productivity.
• Designed an internal on-demand monitoring platform based on Elastic stack and Redis, deployed on top of Kubernetes, to empower teams to effortlessly monitor their applications and systems with minimal setup requirements.