Pura

Senior Data Engineer

Dutch Engineer

I can write blog posts, LinkedIn posts, demos, or share advice about your data or machine learning infrastructure.

Founder

EcZachly Inc

Instructor and Lead Teacher Assistant

Zwift

Build long-term roadmaps for machine learning platform and code best practices for the data science team
Orchestrated the implementation of DBT to build data lineage and shorten debugging time by 30%
Deployed XGBoost models to identify customers who will might or not subscribe in free trials. 
Lead a team to provide the best short-term and long-term solutions to reduce service downtime by 50%
Own e-commerce datasets to lower handle data quality, data contracts, and resolve pipelines downtime
Tools: AWS, Kafka, Python, Docker, Kubernetes, Scala, Spark, SQL, Airflow, Jenkins,  DBT

Senior Data and ML Platform Engineer

Clinical Trial Media

Documented technical specifications of workflows to be presented to stakeholders and executive team
Automated and optimized existing workflows using Prefect and dbt to adhere to best practices
Tools: DBT, Prefect, Azure, Azure Data Factory, Python, SQL, Tableau Server, Docker

Qumulo

Lead migration of on-premise pipelines to cloud capable of handling 210+ GB per day
Produce key metrics to counsel sales and engineering and drive product feature decisions
Integrate linters, tests, and CICD to improve Data Science code quality 
Tools: AWS, Redshift, S3, Postgresql, Pyspark, Fargate, Python, Gitlab CICD, SQL, MongoDB, Tableau

Data Scientist

Blueprint Technologies

Created 30,000 customers’ metric sheets that calculated employees behavior for 1.5 months before and 1.5 months after covid and presented to the c-executive suite of the F500 company 
Developed daily pipelines with >500 TB that build employee behavior metric sheets on request
Productionalize Decision Tree and Logistic Regression to prioritize likely buyers
Optimize SQL and PowerShell scripts to reduce running script from 3 days to 15 minutes.

Tools: Azure Databricks, Python, Plotly, PowerShell, C#, COSMOS, SQL

Data Engineer

Redapt Inc

Migrating Hadoop cluster on VMs to Google Cloud Platform's Dataproc cluster
Importing, cleaning, and visualizing data in Power BI dashboards
Building a storage infrastructure system to identify frequent patterns and errors 
Incorporating Machine Learning algorithms to recommend new items for over a million items and for several thousands of customers. 
Tools: Hadoop, Kafka, Airflow, Spark, Power BI, Azure Databricks, Azure ML Studio, Azure Blob Storage

Apex Learning

Build a python script to obtain Zendesk's data via its RESTful API for marketing reports
Redesigned monthly and yearly reports by incorporating Tableau Software to evaluate tutors’ performance 
Implement Salesforce.com to create an easily accessible school’s credit acceptance database for marketing campaigns 
Support middle and high school students’ through the Apex Learning Virtual School curriculum

Online Tutoring and Data Analysis

Projects

ILest: Ionic Liquid estimation Tool
Team project, Implemented LASSO, SVR, and MLP-Regressor on 10,000 data points to estimate the desired properties of ionic liquid binary mixtures for electric battery applications
Tools: scikit-learn, Pandas, RDKit, Matplotlib

Data-Driven Design of Perovskite
Team Project, Carried out LASSO, and supervised neural networks on a reduced data set to identify the optimal combination of elements in the hybrid organic perovskites (crystals)
Tools: scikit-learn, Pandas, RDKit, Matplotlib

Stack Overflow: Suggest a Tag for My Post Please 
Queried 150k posts and users details to determine tags needed based upon a posts' body or score.
Tools: PySpark, Neo4j, Plotly, Python, Cypher, SQL

How Much Will Your Videogame Sell For? 
Web scraping video game tweets and statistics from VGChartz to predict their unit sales using machine learning
Tools: BeautifulSoup, Matploblib, multiprocessing, requests, plotly

Twitter Scraping Tool
Web-scraped old tweets from the twitter page to eliminate the usage of the Twitter Official API and decrease the time needed by 60%. Tools: pyquery, requests, datetime

Senior Data & ML Platform Engineer | dutchengineer.substack.com | Host of Ask A Data Mentor Podcast

Built long-term roadmaps for data platform and machine learning platform
Experience in designing, analyzing, and visualizing large (>500 TB) datasets 
Build and manage multiple ETL infrastructures to identify text patterns and detect network and hardware anomalies
Prepare critical metrics to guide product decisions in people, healthcare, computer games, and chemical analytics
Multilingual (Dutch, English, Spanish)

Keywords: Airflow, AWS (Cloudwatch,  ECS, EKS, Fargate, Glue, Redshift, Kinesis, Databricks, Postgresql, S3), Azure (Azure Functions, Azure ML Studio, Databricks, PowerBI, SQL Server), BentoML, C++, Datadog, Docker, ElasticSearch, Flink, Kafka, Keras, Kubernetes, Hive, High Performance Computing, Github Actions, Gitlab CICD,  Pagerduty, PowerBI,  Prefect, Python (DBT, Numpy, Pydantic, Sklearn,Scipy), Pyspark, Neural Network, Natural Language Processing, MLFlow, MongoDB, Recommendations, Sagemaker, Scala, SparkML, SQL, Tableau, Terraform

Good morning everyone! 

Within 2 weeks of getting laid off, I ended up with four offers, two data engineering and two machine learning engineering. 

As someone who just finished this experience, I would love to answer questions you all might have. 

Comment below 👇 

#dataengineer #data #machinelearning 

Sarah Floris, MS

What are the key skills required for a data engineer?

Last week, I shared that I had received 4 job offers in machine learning and data engineering after just 2 weeks of job searching. 

I received a lot of comments and questions about how I was able to achieve this and will answer them in following up posts.  

Before I do, I want to cover some of the factors that come into play when applying for jobs and receiving offers. 

1. Location
Location matters whether that is the number of remote jobs or the location in which you are applying in jobs. Moving from other cities and countries can have a negative effect on your job search.

I have been in Seattle, a huge tech hub for remote and in-person positions, for the last few years. 

2. Immigration status
Whether you need a visa or not greatly determines the number of opportunities that are available to you. See the next bullet. 

3. Size of the company
Smaller companies typically do not sponsor visas, so candidates who need that visas have to focus on larger, slower companies. 

These smaller companies tend to have much shorter or quicker turnarounds for their positions.  

4. Experience
Experience also matters. Most of the available positions that I saw for Data Engineer and Machine Learning Engineering required at least 3 years of experience. 

5. Skills
Some skills are in higher demand than others. For example, the infrastructure type skills e.g. familiarity with spark, terraform, docker, and kubernetes are in higher demand right now. Those happen to be the skills I have. 

I hope this sheds some light on why I found it easier to find a job than others. Stay tuned for my upcoming posts where I will answer more of your questions and comments. 

#datascience #data #dataengineer #career

What are the latest tech job trends in Seattle?

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