Hi, I'm Alexander Nettekoven

Senior Data Engineer

With 12 years of experience designing scalable data platforms, ML pipelines, and advanced analytics solutions across healthcare, e-commerce, advertising, and gaming industries. Recently led development of an HR analytics platform integrating predictive workforce modeling and executive dashboards.

Austin, TX 78701
929 233 9976
alexandernettekoven325@gmail.com
LinkedIn Profile GitHub
Alexander Nettekoven - Senior Data Engineer

About Me

I'm a passionate Senior Data Engineer with over a decade of experience building robust, scalable data infrastructure and advanced analytics solutions. My expertise spans the entire data lifecycle, from designing ETL/ELT pipelines to implementing machine learning models in production environments.

Throughout my career, I've had the privilege of working with industry leaders like Google, where I optimized ad targeting systems, and various innovative companies where I've built everything from real-time streaming platforms to predictive analytics dashboards that drive business decisions.

I'm particularly passionate about leveraging data to solve complex business problems, mentoring teams, and staying at the forefront of emerging technologies in the data engineering landscape.

Professional Experience

Senior Data Engineer

Dutech Austin, TX Dec 2021 – Jun 2025
  • Designed and implemented ETL/ELT pipelines with Airflow, dbt, and Snowflake to consolidate HRIS, payroll, and engagement data into a centralized analytics platform
  • Partnered with HR and data science teams to support predictive modeling for attrition and workforce planning, enabling leaders to reduce turnover and optimize staffing strategies
  • Delivered executive dashboards in Tableau and Power BI tracking hiring funnels, diversity metrics, and workforce performance trends
  • Established data governance and access controls to ensure secure handling of sensitive workforce data in compliance with GDPR and SOC2 requirements
  • Built real-time streaming pipelines with Kafka and Spark to process billions of iGaming transactions and player interactions
  • Developed fraud detection and anomaly detection pipelines to flag high-risk gaming activity, preventing financial losses and improving platform integrity
  • Led migration of legacy iGaming systems into BigQuery and Databricks, reducing infrastructure costs by 30% while scaling to high-volume workloads

Senior ML & Data Engineer

Google Austin, TX Mar 2020 – Oct 2021
  • Engineered ML pipelines for Google Ads optimization, leveraging TensorFlow Extended (TFX), Kubeflow, and Apache Beam to improve ad targeting and bidding
  • Built a real-time feature store capturing clickstream, keyword, and campaign data, cutting feature duplication and reducing model delivery time by 40%
  • Designed low-latency Dataflow and BigQuery pipelines to process billions of impressions daily, enabling timely signals for ad-serving models
  • Partnered with research teams to productionize deep learning models that improved click-through rate (CTR) predictions and ad relevance
  • Implemented monitoring and drift detection systems that safeguarded predictive accuracy across diverse ad markets and geographies
  • Optimized distributed TPU training workflows, cutting training time by 30% and reducing costs by $1M annually
  • Developed A/B testing frameworks for ad-ranking models, enabling safe rollouts and rapid rollback of underperforming models
  • Migrated critical ML workflows to Vertex AI, accelerating deployment velocity and improving standardization across Google Ads teams
  • Authored design docs and best practices that unified ML engineering approaches across multiple Google Ads teams

Senior Data Scientist

BigCommerce Austin, TX Dec 2018 – Dec 2019
  • Built and deployed recommendation algorithms for upsell and cross-sell strategies, increasing average order value by 10%
  • Designed churn prediction models using gradient boosting and logistic regression, driving retention campaigns that saved millions in recurring revenue
  • Developed fraud detection models with anomaly detection, reducing false positives in flagged transactions by 18%
  • Partnered with product teams on A/B and multivariate experiments, introducing statistical rigor to validate feature rollouts
  • Created customer segmentation models with clustering methods, enabling personalized marketing that boosted engagement rates
  • Optimized model training pipelines in Python and Spark, cutting experimentation cycles by 40% and accelerating model delivery
  • Presented executive-level dashboards and data stories linking predictive insights to business outcomes, shaping roadmap decisions

Data Analyst

Nomi Health Austin, TX Jan 2015 – Oct 2018
  • Designed and maintained SQL reporting pipelines for claims, billing, and patient records, improving data quality and operational reporting accuracy
  • Built interactive dashboards in Tableau/Power BI to monitor provider performance, patient throughput, and key healthcare KPIs
  • Partnered with finance teams to detect anomalies in claims data, identifying $2M+ in cost savings and strengthening fraud prevention
  • Automated recurring reporting workflows in Python (pandas, NumPy), cutting manual preparation by 60% and enabling faster analysis cycles
  • Developed early predictive models in Python/R to forecast patient demand and optimize clinic staffing
  • Applied classification techniques on patient outcomes to identify high-risk populations and improve proactive care strategies
  • Used basic NLP methods to extract insights from clinical notes, informing adherence and treatment effectiveness studies
  • Supported migration to AWS Redshift, improving query performance and enabling large-scale healthcare analytics adoption

Junior Backend Developer

SailPoint Technologies Austin, TX Nov 2013 – Oct 2014
  • Contributed to designing and maintaining relational schemas for identity and access management systems, ensuring normalized structures and consistent business rules
  • Wrote and debugged SQL queries, stored procedures, and triggers that supported reporting and authentication services
  • Optimized indexing and query execution plans, improving query performance by ~25% in production workloads
  • Assisted in database migration from Oracle to PostgreSQL, achieving zero data loss and <2 hours downtime
  • Partnered with senior developers to integrate backend modules with the database layer, reinforcing data consistency and integrity
  • Reduced recurring reporting errors by 15% by introducing data validation checks and process documentation

Key Projects & Achievements

Enterprise HR Analytics Platform

Dutech (2021-2025)

Led the design and implementation of a comprehensive HR analytics platform consolidating HRIS, payroll, and engagement data using modern data engineering technologies.

Predictive workforce modeling and attrition analysis
ETL/ELT pipelines with Airflow, dbt, and Snowflake
GDPR and SOC2 compliant data governance
Airflow dbt Snowflake Tableau Power BI

Google Ads ML Optimization Platform

Google (2020-2021)

Engineered production ML pipelines processing billions of ad impressions daily to improve targeting and bidding algorithms using cutting-edge technologies.

40% reduction in model delivery time
$1M annual cost savings through TPU optimization
Improved CTR predictions with deep learning models
TensorFlow Extended Kubeflow Apache Beam BigQuery Vertex AI

Real-time iGaming Analytics Platform

Dutech (2021-2025)

Built real-time streaming pipelines processing billions of gaming transactions with fraud detection and anomaly detection capabilities.

Real-time processing of billions of transactions
30% infrastructure cost reduction
Advanced fraud detection algorithms
Kafka Spark BigQuery Databricks Python

E-commerce Recommendation Engine

BigCommerce (2018-2019)

Developed recommendation algorithms for upsell and cross-sell strategies, along with churn prediction models to improve customer retention.

10% increase in average order value
40% faster experimentation cycles
18% reduction in fraud false positives
Python Scikit-learn Spark SQL A/B Testing

Healthcare Analytics & Cost Optimization

Nomi Health (2015-2018)

Built comprehensive healthcare analytics platform with SQL reporting pipelines, interactive dashboards, and predictive modeling for patient outcomes.

$2M+ cost savings through anomaly detection
60% reduction in manual reporting time
Improved proactive care strategies
SQL Python R Tableau AWS Redshift

Enterprise Database Migration

SailPoint Technologies (2013-2014)

Led database migration from Oracle to PostgreSQL for identity management systems, achieving zero data loss and minimal downtime.

Zero data loss migration
<2 hours downtime
25% improved query performance
Oracle PostgreSQL SQL Optimization Data Migration Performance Tuning

Technical Skills

Data Engineering & ETL/ELT

ETL/ELT Pipelines Data Modeling Data Warehousing dbt Apache Airflow Apache Spark Kafka Databricks Hadoop SQL Optimization Data Quality & Governance

Machine Learning & AI

Predictive Modeling Recommender Systems Classification & Clustering Anomaly Detection Natural Language Processing (NLP) TensorFlow PyTorch Scikit-learn MLOps (TFX, Kubeflow, Vertex AI)

Cloud & Big Data Platforms

Google Cloud Platform (BigQuery, Dataflow, Vertex AI) AWS (Redshift, S3, Lambda, Glue) Azure (Synapse, Data Factory) Snowflake Data Lakes Kubernetes Containerized Deployments

Programming & Tools

Python (pandas, NumPy, PySpark) SQL (PostgreSQL, MySQL, Oracle) R Shell Scripting Git CI/CD Pipelines API Development REST/GraphQL Integration

Analytics & Visualization

Tableau Power BI Looker Executive Dashboards Experiment Design (A/B & Multivariate Testing) Statistical Analysis Business Intelligence Strategy

Soft Skills & Leadership

Cross-functional Collaboration Client-Facing Consulting Technical Mentorship Documentation & Knowledge Sharing Agile/Scrum Practices Data-Driven Decision-Making

Education

Bachelor's Degree, Computer Science

The University of Texas - Austin 2009 – 2013

Let's Connect

I'm always interested in discussing new opportunities, collaborating on exciting projects, or sharing insights about data engineering and machine learning.

Email

alexandernettekoven325@gmail.com

LinkedIn

alex-nettekoven

GitHub

alex-nettekoven

Phone

929 233 9976