Open to opportunities

Farsh Ebady

@farshebady

Senior Data Engineer and Data Architect with 9+ years building enterprise lakehouse, ETL/ELT, and real-time integration platforms.

United States

Message

What I'm looking for

I’m looking for a role where I can design governed, cost-efficient data platforms and real-time ETL/ELT pipelines, modernize legacy systems to cloud-native architectures, and partner with AI/BI stakeholders—while leading delivery with strong engineering standards and observability.

I’m a Senior Data Engineer and Data Architect with 9+ years of progressive experience delivering enterprise-grade data warehousing platforms, ETL/ELT pipelines, and real-time data integration architectures. I translate complex business requirements into scalable, governed, and high-performance data ecosystems using Databricks, Snowflake, Apache Spark, Kafka, Palantir Foundry, AWS, and Azure.

I consistently cut query costs, eliminate pipeline failures, and reduce time-to-insight. From building governed medallion lakehouses (Bronze/Silver/Gold) with Unity Catalog to modernizing legacy ETL into cloud-native, fault-tolerant distributed platforms, I ensure data platforms are trusted by the business through observability, lineage, and validation.

I lead cross-functional engineering teams, run client discovery workshops, and drive architecture roadmaps from discovery through delivery—aligning data infrastructure with AI, machine learning, and business intelligence strategies.

Experience

Work history, roles, and key accomplishments

Current

Data Architect

Current

Lovelytics

Feb 2022 - Present (4 years 5 months)

Owned end-to-end lakehouse and data platform architecture on Databricks/Unity Catalog/Delta Lake across AWS and Azure, integrating Palantir Foundry with governed lineage and access controls. Standardized ingestion and CDC from 20+ heterogeneous sources and established governance frameworks, while cutting infrastructure provisioning time via Databricks/Spark and CI/CD automation.

Unity Catalog Delta Lake Palantir Foundry Apache Spark Kafka Terraform CI CD Data Governance CDC ETL ELT

Data Engineering Lead

Together AI

Dec 2019 - Jan 2022 (2 years 1 month)

Led data engineering for AI product data platforms, architecting high-throughput Kafka-based ETL/ELT processing tens of millions of events daily with sub-second latency targets. Delivered real-time analytics that reduced time-to-insight by 60% and optimized Snowflake costs by 40%+ through query tuning and data model improvements.

Apache Kafka AWS Lambda Python Snowflake Real Time Analytics ETL ELT Distributed Data Processing Data Modeling DBT

Senior Data Engineer

Firstbase

Oct 2016 - Nov 2019 (3 years 1 month)

Designed and built production ETL pipelines in Python/Airflow with AWS services (S3, Glue, Lambda) to automate ingestion from 15+ sources into a centralized Snowflake warehouse. Improved reliability and self-serve analytics by reducing manual processing overhead by 70%, cutting ad-hoc data requests by 50%, and maintaining 99.9%+ pipeline uptime through logging and proactive anomaly detection.

Python Apache Airflow AWS S3 AWS Glue AWS Lambda Snowflake DBT Terraform Docker

Data Analytics Engineer

Inspiren

Apr 2015 - Sep 2016 (1 year 5 months)

Built scheduled batch ETL using Python/Pandas to move and transform data from PostgreSQL/MySQL into reporting layers, supporting operational reporting and executive dashboards. Created dimensional models and Tableau/KPI dashboards that reduced ad-hoc reporting requests by 40%, while improving reporting accuracy via validation and data quality checks.

Python (Pandas)SQL PostgreSQL MySQL Data Modeling Tableau Data Validation Stored Procedures