You will get a Databricks cost & performance audit from a certified professional
Rising Talent
Project details
Is your Databricks bill creeping up, or are your pipelines slower than they should be? I'll audit your workspace and give you a prioritized, quantified action plan.
I'm a Databricks Certified Data Engineer Professional (plus GenAI Engineer, ML, and Data Analyst Associate certifications) working daily on enterprise Databricks implementations. I also presented my own end-to-end Lakehouse project at JEDAI, the official Databricks community event in Japan — full source code is public on my profile.
What I review:
• Cluster configuration & policies (right-sizing, autoscaling, spot usage, Photon)
• Job & DLT compute choices and scheduling
• Storage layout: partitioning, liquid clustering, OPTIMIZE/VACUUM cadence
• Query and PySpark anti-patterns (shuffles, skew, caching)
• Unity Catalog and governance quick wins
What you get: a written report with findings ranked by impact, estimated savings, and concrete fixes — plus a walkthrough call if you want one.
Fully bilingual (English/Japanese) — ideal if your team or data touches the Japanese market.
I'm a Databricks Certified Data Engineer Professional (plus GenAI Engineer, ML, and Data Analyst Associate certifications) working daily on enterprise Databricks implementations. I also presented my own end-to-end Lakehouse project at JEDAI, the official Databricks community event in Japan — full source code is public on my profile.
What I review:
• Cluster configuration & policies (right-sizing, autoscaling, spot usage, Photon)
• Job & DLT compute choices and scheduling
• Storage layout: partitioning, liquid clustering, OPTIMIZE/VACUUM cadence
• Query and PySpark anti-patterns (shuffles, skew, caching)
• Unity Catalog and governance quick wins
What you get: a written report with findings ranked by impact, estimated savings, and concrete fixes — plus a walkthrough call if you want one.
Fully bilingual (English/Japanese) — ideal if your team or data touches the Japanese market.
Machine Learning Tools
Apache Spark, Databricks Platform, Databricks MLflowWhat's included
| Service Tiers |
Starter
$150
|
Standard
$400
|
Advanced
$900
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 2 |
Model Validation/Testing | - | - | - |
Model Documentation | |||
Data Source Connectivity | - | - | |
Source Code | - | - |
About Kazuki
Databricks Data Engineer | 4x Certified (DE Professional) | RAG/LLM
Yokohama, Japan - 11:56 am local time
I also spoke at JEDAI, the official Databricks user community event in Japan, where I presented an end-to-end Lakehouse platform I built — Discord community analytics with a Bronze/Silver/Gold medallion architecture, DLT, and an LLM-powered app on Databricks Apps. The full project is public on my GitHub (see my portfolio).
WHAT I CAN HELP YOU WITH:
• Data pipelines on Databricks — ETL/ELT with PySpark, Delta Lake, Delta Live Tables, Workflows; medallion architecture
• RAG / GenAI applications — retrieval pipelines, few-shot prompting, LLM integration on Databricks (Certified Generative AI Engineer)
• Data quality & governance — Unity Catalog, quarantine/validation frameworks, compliance-aware design (healthcare experience)
• Analytics & ML — SQL, Python, R; certified Databricks ML Associate and Data Analyst Associate
WHY ME:
• Certified at the Professional level and using Databricks in real enterprise projects daily — not just exam knowledge
• Public proof of work: my JEDAI talk (recording + slides) and the full project repository are linked in my portfolio
• Mathematics & computing science major at Keio University — strong analytical foundation
• Fully bilingual: native Japanese, near-native English (TOEIC 985) — ideal for projects touching the Japanese market or bilingual documentation
I'm new to Upwork, so my rate is set below market while I build my track record here. Happy to start with a small, clearly scoped task so you can evaluate my work with minimal risk.
Steps for completing your project
After purchasing the project, send requirements so Kazuki can start the project.
Delivery time starts when Kazuki receives requirements from you.
Kazuki works on your project following the steps below.
Revisions may occur after the delivery date.
Scope & access
You answer a few questions about your setup (cloud, workloads, main pain points) and share read-only workspace access or exports (cluster configs, job run metrics, query profiles). I confirm scope within 24 hours.
Audit & analysis
I review compute configuration, job scheduling, storage layout, table maintenance, and query patterns — measuring actual usage data, not guesswork. I flag anything urgent immediately instead of waiting for the report.