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Ana Mason User

@anamasonuser1

Lead Data Engineer specializing in Databricks lakehouse platforms, Kafka streaming, and healthcare-compliant data governance.

United States

Message

What I'm looking for

I’m looking to lead data platform teams building compliant lakehouse and streaming systems—governed with Unity Catalog and RBAC, observable end-to-end, and aligned to business outcomes, with room to integrate emerging MLOps/LLMOps and RAG pipelines.

I’m a Lead Data Engineer with nine years of experience designing and delivering enterprise-scale data platforms across healthcare, financial services, and technology. I architected a multi-tenant lakehouse platform using Databricks, Snowflake, and ClickHouse, standardizing Medallion (Bronze–Silver–Gold) ingestion and transformation frameworks to improve reliability across engineering teams.

I build secure, compliant pipelines end-to-end—FHIR/HL7 ingestion with schema validation, Unity Catalog governance with fine-grained RBAC, lineage tracking, audit logging, and PHI masking—while implementing real-time architectures with Apache Kafka and Spark Structured Streaming processing millions of events per hour. I’ve also led teams from 4 to 11 engineers, reduced annual cloud platform spend by 35%, and built multi-cloud data architectures spanning Snowflake, Redshift, BigQuery, and ClickHouse with Spark, dbt, and strong observability.

Experience

Work history, roles, and key accomplishments

Current

Lead Data Engineer

Current

Mind Moves

Feb 2024 - Present (2 years 2 months)

Architected a multi-tenant lakehouse platform on Databricks, Snowflake, and ClickHouse, processing 8–15 TB of clinical and operational data daily. Built Kafka-based real-time streaming pipelines, established Unity Catalog governance with fine-grained RBAC and PHI masking, and reduced annual cloud spend by 35% while scaling the team from 4 to 11 engineers.

Databricks Snowflake Clickhouse Delta Lake Apache Kafka Spark Structured Streaming Unity Catalog RBAC PHI Masking

Senior Data Engineer

CTG

Nov 2019 - Feb 2024 (4 years 3 months)

Designed multi-cloud enterprise data architecture across Snowflake, Redshift, BigQuery, and ClickHouse processing 5 TB of daily workloads. Improved warehouse query performance by 45% and reduced pipeline failure rates by 55% by implementing event-driven ingestion, Spark/dbt transformations for 200+ users, and an observability stack with Datadog/Prometheus/Grafana.

Snowflake Redshift BigQuery Clickhouse Apache Kafka Google Pub Sub Apache Spark DBT Terraform Datadog

Data Engineer

Blue Acorn

May 2018 - Nov 2019 (1 year 6 months)

Architected Kafka-based streaming pipelines handling 200M+ daily events with enhanced throughput, fault tolerance, and resiliency. Built Spark Structured Streaming jobs and near real-time CDC pipelines with Debezium, and improved query performance by 45% via Snowflake schema clustering and micro-partitions.

Apache Kafka Spark Structured Streaming Snowflake Debezium Apache Airflow Terraform Pyspark Python

Junior Data Engineer

Waffle House

Jan 2017 - May 2018 (1 year 4 months)

Built and maintained Python/SQL/SSIS ETL pipelines for multiple operational data sources and developed dimensional warehouse models using Star Schema and SCD Type 2. Optimized complex SQL through indexing, execution-plan analysis, and partition pruning to improve performance by 60%.