Senior Data Analyst I

🇮🇳 Bengaluru, Karnataka 🕑 Full-Time 💰 TBD 💻 Data Science 🗓️ August 14th, 2026

Pandas Power BI PySpark

Edtech.com's Summary

Elsevier is hiring a Senior Data Analyst. The role involves independently conducting complex analyses using Databricks, Snowflake, SQL, and Python, collaborating with Product Owners and Data Scientists to analyze large datasets and generate advanced insights and recommendations that support the development of data products.

Highlights

Deliver complex analytical activities using Databricks, Snowflake, SQL, and Python.
Support Product Owners and Data Scientists in the Research Data Platform domain.
Analyze large datasets to answer technical and business questions.
Perform large-scale data preparation for hypothesis testing and algorithm validation.
Build and maintain relationships with Product Managers and Data Scientists, providing status updates and presenting findings.
Require proficiency in Databricks, Python (including Pandas and PySpark), Apache Spark, Snowflake, JIRA, Tableau, and Power BI.
Minimum of 5 years experience in business intelligence, data engineering, analytics, or a related field.
Strong SQL skills managing large and complex datasets.
Deep understanding of data-quality metrics, analytical validation, and root-cause analysis.
Work contributes to products such as Scopus and SciVal within Elsevier’s Global Operations DataOps team.

Senior Data Analyst I Full Description

About Our Team
The Content and Data Analytics team is part of DataOps within Global Operations at Elsevier, providing analytics services primarily using Databricks and supporting Product Owners, Product Managers, Data Scientists, and Research Data Platform domain teams, contributing to products including Scopus and SciVal.

About the Role
As a Senior Data Analyst, you will independently deliver complex analytical activities using Databricks, Snowflake, SQL, Python, and related technologies, working with Product Owners and stakeholders to analyse large datasets, create advanced-level insights and recommendations, and support the development of data products.

Responsibilities

Support Product Owners or Data Scientists working within the domains of the Research Data Platform.
Analyze large datasets to answer questions from Product Owners or Data Scientists.
Perform large-scale data preparation to test hypotheses, support prototypes, and review precision and recall of data science algorithms.
Build and maintain strong relationships with Product Managers and Data Scientists, presenting achievements and status updates.

Requirements

Expected skills: Databricks, Python, Pandas, PySpark, Apache Spark, Snowflake, JIRA, Tableau, Power BI.
Minimum of 5 years of work experience in business intelligence, data engineering, analytics, data analysis, or related discipline.
Strong SQL skills, including experience working with large and complex datasets.
Strong understanding of data-quality dimensions, analytical validation, and root-cause analysis.

About the Business
Elsevier is a global leader in information and analytics, helping researchers and healthcare professionals advance science and improve health outcomes for the benefit of society.

Original Job Description

Responsibilities

Support Product Owners or Data Scientists working within the domains of the Research Data Platform.
Analyze large datasets to answer questions from Product Owners or Data Scientists.
Perform large-scale data preparation to test hypotheses, support prototypes, and review precision and recall of data science algorithms.
Build and maintain strong relationships with Product Managers and Data Scientists, presenting achievements and status updates.

Requirements

Expected skills: Databricks, Python, Pandas, PySpark, Apache Spark, Snowflake, JIRA, Tableau, Power BI.
Minimum of 5 years of work experience in business intelligence, data engineering, analytics, data analysis, or related discipline.
Strong SQL skills, including experience working with large and complex datasets.
Strong understanding of data-quality dimensions, analytical validation, and root-cause analysis.