Looking for Principal Data analyst, expertise in Healthcare domain
Budget: $8 – $15 USD
I’m deep into a set of large-scale clinical-trial datasets and need a seasoned partner who can move effortlessly from raw tables to polished Tableau dashboards. The stack is Google Cloud Platform (BigQuery in particular), Amazon Redshift, advanced SQL, and Python, so you should feel at home optimizing long, complex queries, tuning warehouse performance, and scripting repeatable data-quality checks.
Where you’ll start
I already have a working schema, but it’s straining under growing volume and new KPI requests. You’ll review the existing models, refactor where necessary, and introduce best-practice partitioning and clustering so queries run in seconds, not minutes. From there, we’ll design consumable, high-performance Tableau workbooks that clinicians can explore without waiting for spinning wheels.
Day-to-day collaboration
We’ll meet briefly each day to prioritise tickets—anything from diagnosing a slow funnel report to wiring up a brand-new metric. I’ll lean on your judgement for real-time troubleshooting and for spotting opportunities to streamline our pipeline or cache results intelligently.
Key expectations
• Translate clinical trial requirements into scalable data models on BigQuery/Redshift
• Write, test, and document advanced SQL that balances readability with speed
• Build intuitive Tableau dashboards, applying extracts or live connections where they fit best
• Use Python when automation, data wrangling, or custom analytics fill a gap that SQL alone can’t cover
• Share practical guidance with me as we iterate, so improvements stick long after each sprint
Acceptance criteria
1. Core dashboards load in under five seconds for standard filter combinations.
2. Longest running analytical query executes in under one minute on a representative dataset.
3. All new tables include clear documentation of grain, joins, and update cadence.
4. Hand-off package (SQL, Python scripts, and Tableau workbooks) passes a code walkthrough with zero critical findings.
If healthcare analytics—and the quirks of clinical trial data in particular—are second nature to you, let’s talk and get this moving.
Where you’ll start
I already have a working schema, but it’s straining under growing volume and new KPI requests. You’ll review the existing models, refactor where necessary, and introduce best-practice partitioning and clustering so queries run in seconds, not minutes. From there, we’ll design consumable, high-performance Tableau workbooks that clinicians can explore without waiting for spinning wheels.
Day-to-day collaboration
We’ll meet briefly each day to prioritise tickets—anything from diagnosing a slow funnel report to wiring up a brand-new metric. I’ll lean on your judgement for real-time troubleshooting and for spotting opportunities to streamline our pipeline or cache results intelligently.
Key expectations
• Translate clinical trial requirements into scalable data models on BigQuery/Redshift
• Write, test, and document advanced SQL that balances readability with speed
• Build intuitive Tableau dashboards, applying extracts or live connections where they fit best
• Use Python when automation, data wrangling, or custom analytics fill a gap that SQL alone can’t cover
• Share practical guidance with me as we iterate, so improvements stick long after each sprint
Acceptance criteria
1. Core dashboards load in under five seconds for standard filter combinations.
2. Longest running analytical query executes in under one minute on a representative dataset.
3. All new tables include clear documentation of grain, joins, and update cadence.
4. Hand-off package (SQL, Python scripts, and Tableau workbooks) passes a code walkthrough with zero critical findings.
If healthcare analytics—and the quirks of clinical trial data in particular—are second nature to you, let’s talk and get this moving.
Related categories:
Python
SQL
Big Data Sales
QlikView
Data Warehousing
Tableau
Data Analysis
PySpark
Data Modeling
BigQuery