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Asha Khan

@ashakhan

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Lead Data Engineer modernizing cloud lakehouses into trusted, governed data products for analytics and AI.

United States

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What I'm looking for

I’m looking to lead cloud-native data engineering and lakehouse/Data Mesh modernization with strong governance. I want to build reliable batch/streaming pipelines, partner with security and product, and mentor teams to deliver trusted analytics and AI-ready data.

I’m a Lead Data Engineer and Data Architecture specialist with 10 years of experience designing, building, and scaling enterprise-grade data ecosystems. I focus on end-to-end cloud-native data engineering and lakehouse architecture across AWS, Azure, GCP, and Snowflake.

I bridge high-level architecture with hands-on delivery of high-performance batch and streaming platforms using Python, SQL, Spark, Databricks, Kafka, and Airflow. I’ve enabled analytics, machine learning, and Generative AI platforms by transforming raw data into trusted, business-ready assets—at petabyte scale.

My work consistently modernizes legacy platforms into Data Mesh and Medallion architectures while implementing enterprise governance, security, metadata management, lineage, and FinOps frameworks. I build data reliability engineering practices, including observability, data quality frameworks, SLA monitoring, and pipeline resiliency.

Across projects, I lead architectural decisions, code reviews, and performance tuning initiatives, partnering with executives, security, and product teams to align data architecture with business capabilities. I’m especially energized by building governed, cost-optimized, cloud platforms that keep analytics and AI teams productive.

Experience

Work history, roles, and key accomplishments

Senior Data Architect

ProCogia

Aug 2019 - Dec 2022 (3 years 4 months)

Led enterprise multi-cloud data architecture for analytics ecosystems across AWS, Azure, Snowflake, and GCP, defining ingestion, processing, storage, governance, security, and consumption layers. Built reference architectures for lakehouse, Data Mesh/Medallion, and event-driven real-time streaming using Kafka/Flink/Spark Streaming, including metadata, lineage, and FinOps-driven cost optimization.

Data Architecture Lakehouse Architecture Apache Kafka Apache Flink Data Governance Data Lineage FinOps Security Compliance

Data Engineer

Enigma Technologies

Jun 2016 - Jul 2019 (3 years 1 month)

Developed scalable distributed data pipelines using Python, SQL, Spark, Airflow, and Hadoop ecosystem technologies, building enterprise data lakes and analytical warehouses. Implemented batch and streaming ingestion from databases, APIs, SaaS systems, and log sources, and delivered trusted models with validation, reconciliation, monitoring, and BI support.

ETL ELT Python SQL Apache Spark Apache Airflow Hadoop Ecosystem Data Modeling DBT

Data Engineer

Datafold

Jan 2014 - May 2016 (2 years 4 months)

Built foundational ETL pipelines and enterprise data warehouse solutions using SQL, Python, and scripting frameworks, ingesting data from ERP/CRM platforms, flat files, and third-party sources. Created reporting datasets and analytical views while supporting dimensional modeling, metadata/documentation, scheduling, data quality checks, reconciliation, and production issue resolution.