WUWade User
@wade
Data Engineering Lead with 9+ years building secure, scalable lakehouse and streaming platforms.
United StatesWhat I'm looking for
I’m a Data Engineering Lead with 9+ years designing and delivering scalable, high-performance data platforms across healthcare and enterprise environments. I’m deeply hands-on with Azure, Databricks, and Snowflake, and I focus on turning complex data challenges into reliable, cost-efficient solutions that drive business value.
In my current role, I lead data engineering strategy and platform architecture for healthcare and enterprise clients, including a multi-tenant lakehouse on Databricks and Snowflake processing 8–15 TB of data daily. I’ve improved query performance by 40%, strengthened reliability to 99.9% SLA, and cut operational costs by 35% through cloud-native migration, lakehouse optimization, and performance tuning across Spark workloads.
I also specialize in real-time and governed data flows—building Kafka streaming pipelines, CDC synchronization, and HIPAA-compliant EHR ingestion frameworks (HL7 v2/v3 and FHIR), including RBAC, PHI masking, encryption, and row-level security. I’ve led and mentored teams of 8–10 engineers while delivering ETL/ELT modernization and large migrations on time and within budget, using infrastructure-as-code (Terraform) and CI/CD to keep platforms dependable.
Experience
Work history, roles, and key accomplishments
Lead Data Engineer
Fynite
Jul 2023 - Present (2 years 9 months)
Architected and deployed a multi-tenant Databricks/Snowflake lakehouse processing 8–15 TB daily, improving query performance by 40% via partitioning, Z-Ordering, and cluster auto-scaling. Led Azure-native migration and platform optimization, cutting operational costs 35% and improving reliability to 99.9% SLA while reducing job runtime 45% and dashboard latency 70% with ClickHouse, including end-t
ACDelivered real-time data platform solutions by designing Kafka streaming pipelines ingesting 200M+ events daily and building Spark Structured Streaming jobs with checkpointing and idempotent logic for fault-tolerant, exactly-once delivery semantics. Optimized ClickHouse and Snowflake for large-scale analytics (storage -25%, query latency -40%, query time -45%) and implemented CDC with Debezium/Kaf
Data Engineer
Agit AI
Apr 2017 - Feb 2019 (1 year 10 months)
Designed and delivered ETL pipelines processing 3B+ historical records for regulatory reporting and analytics, reducing processing time by 60% using parallelization and partition pruning. Built dimensional warehouse models with SCD Type 2 for point-in-time reporting, improved query performance by 60% through SQL optimization, and increased nightly batch reliability from 87% to 99.5% using Airflow
Education
Degrees, certifications, and relevant coursework
Wade hasn't added their education
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