BI Tech Lead

Thermo Fisher

Quick summary

Work type: On-site
Location: Lagunilla, Costa Rica
Posted: 3 days ago
Nearby: 1 role within 25 mi

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Salary context

How this pay compares to similar roles

Similar $184k

$141k most similar roles pay here $223k

This listing doesn't post a salary. Most similar roles pay $157,450–$211,200.

Based on 239 similar postings.

Employer

About Thermo Fisher

Thermo Fisher Scientific is the world leader in serving science, providing analytical instruments, equipment, reagents, consumables, software, and services for life sciences research, pharmaceutical manufacturing, and diagnostics. Industry: Life Sciences & Laboratory Equipment

Thermo Fisher currently has 16 open roles on FindRole.

Listed pay typically runs $133,744–$171,900 across 12 roles with salary data.

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At a glance

TL;DR · BI Tech Lead

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The Lead Data Engineer – Supply Chain Analytics role within the supply chain team requires an experienced professional with 10-12+ years of hands-on expertise in building scalable ETL/ELT pipelines, integrating data from ERP, CRM, and other systems using cloud platforms like AWS, Databricks, and Redshift. Day-to-day responsibilities include developing robust data ingestion workflows, ensuring data quality and reliability, and enabling analytics for operational decision-making. The candidate will collaborate closely with Supply Chain teams to deliver curated datasets aligned with key KPIs, support BI tool dashboards, and contribute to the deployment of machine learning models. Proficiency in SQL, Python, and distributed processing frameworks such as Spark is essential, along with a strong understanding of supply chain processes and data governance standards.

Skills

AWS Databricks Redshift Python SQL Spark Power BI CI/CD SAP PostgreSQL Kafka Terraform Git Jenkins Snowflake Hadoop DataBricks SQL ETL ELT

What you'll do

Design and maintain ETL/ELT pipelines for supply chain systems using cloud platforms.
Develop curated datasets aligned with key supply chain KPIs for analytics enablement.
Implement best practices for data validation, monitoring, and pipeline performance optimization.
Enable near real-time data availability for critical operational use cases in the supply chain.
Apply and enforce data quality checks and governance standards for supply chain datasets.
Support deployment of machine learning models within data pipelines and production environments.

What we're looking for

10+ years of experience in Data Engineering with supply chain exposure.
Expertise in designing and maintaining ETL/ELT pipelines using cloud platforms like AWS, Databricks, Redshift.
Proficiency in SQL, Python, and distributed processing frameworks such as Spark.
Deep understanding of supply chain processes including planning, inventory management, procurement, and logistics.
Experience building datasets and data models for key supply chain KPIs and reporting.
Knowledge of BI tools like Power BI and familiarity with ERP systems (SAP).
Strong skills in data quality checks, governance standards, and master data practices.

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