Tiger Analytics Inc.
Senior Data Engineer
Remote role where the employee must remain based in a particular country.
United States only
Employer listed it 5 weeks ago · Added yesterday
Been open since 5 weeks ago, still being checked, but it has been live a while.
Salary
Not stated
Location
United States only
Timezone
US East
Contract
Full-time
Experience
Senior
Category
Data
This employer didn't state pay. Jobs like this usually pay around $130k–$210k a year, a typical range taken from 270 senior-level data roles on Nomaders that do state pay. It's a guide, not an offer.
Remote flexibility
Work from home
This is a remote role, but the employee must be based in United States. It is work from home rather than work from anywhere.
What the employer says
- Source listing states candidate location: "Chicago, United States, Chicago, Illinois, United States, Chicago, Illinois, United States, Remote"
What Nomaders makes of it
- Residency required in United States
- Payroll and tax are likely handled in that country only
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.
We are seeking an experienced Data Engineer to join our data team. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines, data integration processes, and data infrastructure on AWS cloud. You will collaborate closely with data scientists, analysts, and AI teams to support analytics, machine learning, and Generative AI initiatives across the organization.
Requirements
Key Responsibilities:
Design, develop, and deploy end-to-end data pipelines on AWS using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, and related data platform technologies.
Build and maintain scalable data processing and transformation workflows using Databricks, Apache Spark, and SQL.
Develop and maintain Apache Airflow workflows for pipeline orchestration, scheduling, dependency management, monitoring, and automation.
Integrate and process commercial pharmaceutical data sources such as Xponent, Veeva, MMIT, Plantrak, Specialty Pharmacy, LAAD, and similar sources.
Build and optimize data pipelines supporting pharma KPIs, metrics, analytics, and reporting requirements.
Design and implement data pipelines for AI/ML and Generative AI workloads, including structured and unstructured data preparation.
Enable data pipelines supporting LLM-based applications, vector embeddings, and knowledge retrieval/RAG solutions.
Support migration of legacy data systems and pipelines to modern AWS cloud and lakehouse architectures.
Monitor, troubleshoot, and optimize data pipelines for performance, scalability, reliability, and cost-effectiveness.
Ensure data pipelines meet required standards for data quality, accuracy, consistency, and operational reliability.
Communicate effectively with technical and business stakeholders to understand requirements and translate pharmaceutical business needs into scalable data solutions.
Required Skills:
8+ years of experience in Data Engineering, preferably with experience supporting commercial pharmaceutical/healthcare data environments.
Strong hands-on experience with AWS cloud, Databricks, Spark, and SQL
Strong experience building ETL/ELT data pipelines and large-scale data processing workflows.
Hands-on experience with Apache Airflow for workflow orchestration.
Strong understanding of data modeling, data lake/lakehouse architecture, data ingestion, and transformation frameworks.
Deep knowledge of commercial pharmaceutical data sources: Xponent, Veeva, MMIT, Plantrak, Specialty Pharmacy, LAAD, and other commercial pharma data sources
Strong understanding of pharmaceutical commercial data processes, including: Alignment, Allocation, Split credits, Market basket, Customer universe
Strong understanding of pharma KPIs, metrics, and commercial analytics.
Requirements
- ·Key Responsibilities:
- ·Design, develop, and deploy end-to-end data pipelines on AWS using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, and related data platform technologies.
- ·Build and maintain scalable data processing and transformation workflows using Databricks, Apache Spark, and SQL.
- ·Develop and maintain Apache Airflow workflows for pipeline orchestration, scheduling, dependency management, monitoring, and automation.
- ·Integrate and process commercial pharmaceutical data sources such as Xponent, Veeva, MMIT, Plantrak, Specialty Pharmacy, LAAD, and similar sources.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, work from home, matches where you plan to live and work.
- 2Tailor your CV to the role at Tiger Analytics Inc., mentioning your remote working experience and working hours (US East).
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 1d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
Similar roles
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Free to apply, no account needed.
Typically $130k to $210k per year · You'll be taken to the employer's careers page.