Tiger Analytics
via Workable
Senior Data Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 16h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 26d ago
The date the source published, not the day we noticed it (2026-08-20). Last seen at its source 2h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $160.9k–210k/yr
Middle 50% of 740 listings that do state pay — Engineering · Senior · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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workable employer's own board first seen 10d ago · last seen 2h ago
The listing
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.
- Strong analytical, problem-solving, and data troubleshooting skills.
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.