CTO
2019 - 2022Actiondesk- Developed a spreadsheet application connected to dozens of integrations to make data engineering accessible to non-technical business users and automate their dashboards and reporting.
- Conceived and led the implementation—first committer on every service for a long time—of the entire back end.
- Managed a tech team of up to 10 engineers, including front-end, back-end, DevOps, and QA engineers.
- Built dozens of connectors to databases and various APIs like Stripe, Hubspot, Google Analytics, and Quickbooks.
- Created a formula engine to compute Excel-like formulas. The project was in ScalaJS to work both in the back end and in front end and have the exact same results.
- Maintained a Kubernetes cluster for two years until I hired a DevOps engineer that I managed.
- Implemented a sharing feature to share reports with charts on multiple channels, such as Slack, emails, etc.
Technologies: Scala, Vue, Vuex, TypeScript, Apache Kafka, PostgreSQL, Google BigQuery, WebSockets, Canvas, Redis, Kubernetes, SQL, Data Pipelines, Data Build Tool (dbt), Data Engineering, APIs, Microsoft ExcelData Engineer
2017 - 2019Deezer- Developed and maintained the core ETLs in Scala Spark and streaming pipelines with Kafka and Spark.
- Streamed to process 2.5TB/day to support 50+ engineers, analysts, scientists, and product managers.
- Managed data warehousing on HDFS in ORC, Parquet, and AVRO formats.
- Developed our own scheduler in Python that runs 2,000 jobs per day.
Technologies: Apache Hive, HDFS, Hadoop, Apache Kafka, Spark, Scala, SQL, ETL, Data Pipelines, Data EngineeringData Engineer
2016 - 2017Artefact- Developed ETLs in PySpark in collaboration with data scientists.
- Led as main contributor the internal data collection software processing 500GB per day.
- Performed R&D for a stream processing project using Storm and Kafka.
Technologies: Apache Kafka, Storm, Hadoop, PostgreSQL, Spark, Scala, Django, Python, SQL, ETL, Data Pipelines, Data Engineering, APIsData Scientist
2015 - 2016fifty-five- Optimized item ordering of product listings for major clothing retailers websites.
- Developed user segmentation and buying prediction algorithms.
- Optimized recommender systems parallelizing algorithms (ALS-WR) with CUDA.
Technologies: CUDA, C, BigQuery, Python, R, SQLBack-end Engineer
2014 - 2015Pricing Assistant- Developed an eCommerce page parser.
- Developed product matchers in Python.
Technologies: Pandas, Flask, Python