Lead Data Engineer
Data Engineer
Available for hire
Years of
experience
8+ years
Experience
level
Lead
Available
for
Full-time, Part-time, Contract, Freelance
Available from
16 Apr 2026
I have been working in data engineering and data platform development for over 10 years, designing and building scalable data pipelines, cloud data warehouses, and modern analytics platforms. I have successfully delivered high-performance data solutions that support enterprise analytics, reporting, and data-driven decision making across complex environments. I am now looking for a role where I can continue building robust cloud-based data platforms and contribute to impactful data initiatives. What sets me apart is my ability to combine strong hands-on engineering skills with architectural thinking to deliver reliable, scalable, and business-focused data solutions.
Skills
TensorFlow
SQL
Kafka
GraphQL
gRPC
NoSQL
Lambda
JIRA
Kubernetes
Microservices
OpenAI
jQuery
Jest
Natural Language Processing
Firebase
SQLite
Firestore
Heroku
Git
GitHub
CI/CD
Machine Learning
Infrastructure as a Service
Deep learning
Generative AI
Large Language Models
Python
Go
R
MariaDB
BigQuery
Snowflake
IBM Cloud
Flask
FastAPI
NumPy
Pandas
Scikit
Apache Kafka
PyTorch
Keras
Apache Spark
Hugging Face
Hadoop
Airflow
LangChain
Languages
Employment History
Lead Data Engineer at
Flatiron Health
2021
-
2026
- Directed development of 30+ batch and streaming data pipelines processing 5TB+ daily clinical and operational datasets, enabling analytics and machine learning workloads across research platforms.
- Designed end-to-end data platform architecture integrating 12+ healthcare data sources, delivering curated analytics datasets used by BI and data science teams.
- Translated complex clinical and operational requirements into scalable data platform implementations supporting 100+ analytics dashboards and ML experiments.
- Established data reliability and observability frameworks across 50+ production pipelines, reducing pipeline failure rates by 35% and improving monitoring coverage.
- Delivered feature-ready datasets supporting 20+ machine learning models used for healthcare analytics and research experimentation.
- Mentored 6 data engineers and introduced CI/CD and modular pipeline standards that improved deployment efficiency by 40%.
Senior Data Engineer at
Flare
2018
-
2021
- Engineered 25+ ETL and streaming pipelines integrating data from 10+ operational systems, supporting enterprise analytics and reporting platforms.
- Delivered data ingestion and orchestration workflows that processed 3TB+ daily datasets, producing curated analytics-ready tables for dashboards and ML use cases.
- Created modular transformation frameworks and standardized data models that improved dataset consistency and reduced transformation duplication by 30%.
- Translated stakeholder requirements into production-grade pipelines supporting 80+ internal reports and analytical datasets.
- Optimized warehouse and data lake queries across multi-source datasets, reducing average query runtime by 40%.
- Strengthened data quality monitoring across batch and near-real-time workflows, reducing data incidents by 25%.
Data Engineer at
Uber
2018
-
2018
- Engineered high-throughput Spark pipelines processing billions of daily ride and event records, supporting operational analytics and experimentation platforms.
- Produced analytics-ready datasets used by product analytics teams supporting 50+ operational
dashboards.
- Executed distributed data processing jobs handling multi-terabyte datasets, improving pipeline throughput by 25% through optimized partitioning strategies.
- Converted product and operations requirements into reliable transformation workflows supporting real-time ride analytics and reporting systems.
- Ensured pipeline reliability across 20+ production workflows, implementing validation checks and anomaly detection.
- Supported warehouse environments managing petabyte-scale datasets, resolving pipeline failures and maintaining downstream data availability.
Data Analyst Intern at
MindEase
2017
-
2018
- Analyzed operational and product datasets using SQL and Python, supporting 10+ internal reporting dashboards used by business teams.
- Authored SQL queries and transformation scripts that prepared datasets for product analytics and KPI reporting.
- Produced BI dashboards tracking 15+ key performance indicators, helping product teams monitor usage trends.
- Conducted data validation checks across multiple datasets, identifying data inconsistencies that improved reporting accuracy by 20%.
- Assisted analysts and engineers in preparing datasets for analytics workflows supporting customer behavior analysis.
- Documented datasets and analysis processes improving team knowledge sharing and enabling faster onboarding for new analysts.
Education
Bachelor of Science in Computer Science at
Texas Tech University
2013
-
2016