OpenXData & AnalyticsOfficial Job Posting

Business Intelligence Data Analyst at OpenX

Remote (US)Remote2–5 YearsNot specified

OpenX is a leading global adtech company that helps publishers monetize their digital content across various platforms. As a Business Intelligence Data Analyst on the Finance team, you will be responsible for creating data-driven solutions, developing high-impact dashboards, and partnering with finance and product teams to guide strategic business decisions.

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OpenX Business Intelligence Data Analyst career opportunity

Official Role Details

Role Overview

OpenX is a leading global adtech company that helps publishers monetize their digital content across various platforms.

As a Business Intelligence Data Analyst on the Finance team, you will be responsible for creating data-driven solutions, developing high-impact dashboards, and partnering with finance and product teams to guide strategic business decisions.

Applicant Requirements

Eligibility Criteria & Qualifications

Degree / QualificationB.E / B.Tech / MCA / B.Sc

Eligible BatchesNot specified

Official Eligibility Points

Bachelor's degree in Computer Science, Data Science, Statistics, Finance, or a related quantitative field.
Proven experience as a Data Analyst, BI Developer, or in a similar analytical role.
Strong proficiency in SQL and hands-on experience with modern BI tools such as Looker, Tableau, or Power BI.
Solid understanding of financial concepts, business metrics, and data modeling best practices.

Day-to-Day Deliverables

Key Responsibilities

Data Preparation & Quality

•Design, build, and maintain automated BI dashboards, reports, and data visualizations using modern analytics tools.
•Conduct ad-hoc financial and operational data analysis to support company leadership decision-making.

Analysis, Reporting & Visualization

•Extract, transform, and analyze complex datasets using SQL to provide actionable insights for business stakeholders.

Insights & Stakeholder Communication

•Collaborate closely with finance, product, and engineering teams to define business metrics and technical data requirements.

Technical Qualifications

Required Skills & Technologies

SQLTableau / LookerData ModelingFinancial AnalyticsPythonData VisualizationETL Pipelines

Official Application Method

How to Apply

Submit your application directly through OpenX's verified careers portal.

Review the published role requirements, degree qualifications, and eligible graduation batches above.

Ensure your resume highlights relevant projects and contains working GitHub repository links.

Click the official application button below to open OpenX's direct careers page.

Complete and submit your application directly on the employer's portal.

Apply on OpenX Official Careers Page

You will be directed to OpenX's official careers portal. Career Insights does not process applications or charge any candidate fees.

The specifications above are verified official details published by OpenX. Candidates should verify all final terms, deadlines, and eligibility directly on OpenX's official careers portal before submitting an application.

Career Insights

Recommended Preparation

Independent editorial guidance based on the published role information.

What to Prepare

Evaluate your data analysis and quantitative background against published criteria and hands-on preparation focus areas.

Education & Academic Criteria

Cohort: Eligible: Not specifiedPublished Requirement

Published Requirement

B.E / B.Tech / MCA / B.Sc

Preparation Focus

Hiring evaluations prioritize demonstrable problem-solving, domain competence, and practical project evidence over specific degree pedigree.

SQL & Data Querying

Published Requirement

Proficiency in relational databases, SQL queries, and data extraction.

Preparation Focus

Master complex SQL operations: Window functions (ROW_NUMBER, RANK, DENSE_RANK), CTEs, multi-table JOINs, and query execution plan analysis.

Data Analysis & Visualization

Published Requirement

Data cleaning, transformation, and reporting dashboards.

Preparation Focus

Be prepared to clean messy datasets using Python (Pandas/NumPy) or Excel, identify statistical outliers, and explain KPI metric definitions.

Data Storage & Persistence

Published Requirement

Familiarity with databases, schema modeling, and structured query writing.

Preparation Focus

Be prepared to explain relational normalization (1NF-3NF), indexing trade-offs, foreign key constraints, and transactional consistency.

Version Control & Engineering Hygiene

Published Requirement

Familiarity with Git branching, pull requests, and collaborative repository management.

Preparation Focus

Review Git branch workflows, pull request code reviews, and maintain clean commit history with descriptive messages.

Work Mode & Collaboration

Published Requirement

Remote (Work From Home) operational structure.

Preparation Focus

Highlight proactive written communication, technical documentation discipline, and the ability to troubleshoot errors systematically before escalating.

Technical Topics

Depending on the hiring team’s evaluation style, technical assessments for this role typically cover these core areas:

Topic 1: Advanced SQL & Data Extraction

Preparation Topic

Window functions (ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD)
Common Table Expressions (CTEs), multi-table JOINs, and subqueries
Query optimization, index utilization, and execution plan review

Preparation Tip: Practice writing complex SQL aggregations on paper or in an editor, explaining your reasoning around NULL handling and join cardinalities.

Topic 2: Data Cleaning, Wrangling & Validation

Preparation Topic

Handling missing values, duplicated records, and date/time conversions
Using Python (Pandas/NumPy) or SQL for data hygiene and transformation
Detecting statistical outliers and verifying data distribution integrity

Preparation Tip: Explain your systematic approach to validating a raw dataset before performing any modeling or executive reporting.

Topic 3: Metric Definition, KPI Modeling & Dashboard Architecture

Preparation Topic

Designing intuitive business dashboards (Power BI, Tableau, Looker)
Formulating unambiguous metric definitions (retention, churn, cohort LTV)
Choosing appropriate data visualizations for business decision-making

Preparation Tip: Be prepared to demonstrate how you designed a dashboard so that executives can draw actionable insights within seconds rather than hunting through tables.

Topic 4: Business Problem Solving with Data & Hypothesis Testing

Preparation Topic

Formulating testable hypotheses from operational questions
Segmenting customer or operational cohorts to isolate drivers
Translating statistical patterns into concrete operational recommendations

Preparation Tip: Pick a dataset project from your portfolio and clearly articulate: what was the business question, what did the data reveal, and what decision was made.

Topic 5: Cross-Functional Storytelling & Analytical Communication

Preparation Topic

Explaining data nuances and limitations to non-technical team members
Answering questions about statistical confidence and data provenance
Collaborative iteration with product managers and engineers

Preparation Tip: Frame analytical results around business impact: revenue saved, efficiency gained, or risk avoided.

* Note: These are independent Career Insights editorial recommendations to help candidates structure their study plan. They do not represent guaranteed interview stages or official hiring mandates from OpenX.

Practical Project

Turn the listed data skills into a portfolio exercise using a realistic dataset, analysis workflow, and decision-focused output.

Practical Project

Customer Cohort Retention & Churn Analyzer

Recommended Preparation Project

What to Build

A SQL-driven analytics project that calculates monthly cohort retention, customer lifetime value, and churn indicators from raw transaction tables.

Skills Demonstrated

Advanced SQL (Window Functions, CTEs), Data Modeling, Business Intelligence Visualization, Statistical Analysis

GitHub Deliverables

Include database schema diagrams, reproducible sample data generation scripts, and screenshots of key cohort insights charts.

Interview Talking Points

Query optimization techniques for large event tables and how you accounted for edge cases like returning inactive users.

Career Insights recommendation: This project is an independent editorial recommendation designed to help candidates build verifiable portfolio evidence. It is not required or sponsored by OpenX.

Before You Apply

Verify your dataset portfolios, dashboard presentations, and application materials before applying.

1. Role-Tailored Resume & Data Portfolio Links

Ensure your resume highlights SQL queries, data manipulation projects, and interactive dashboard links involving SQL, Tableau / Looker, Data Modeling.

2. Eligibility & Qualifications Verification

Confirm that your degree, graduation year (Not specified), and location match OpenX's criteria.

3. Data Project & Metric Walkthrough Review

Have 1–2 data analysis projects prepared. Be ready to explain your data cleaning methodology, SQL aggregation queries, and actionable conclusions.

4. Direct Submission on OpenX's Official Portal

Submit your application directly through OpenX's official careers portal using the verified apply link below. Career Insights does not process applications or charge any candidate fees.

Career Growth Context

Editorial analysis of how this role builds quantitative expertise and strategic analytical influence.

Data Architecture & Tooling Orientation

Familiarity with enterprise data warehouses, schema design, SQL data pipelines, and internal business metrics.

Exploratory Analysis & Dashboard Engineering

Constructing performant business intelligence dashboards, validating dataset integrity, and automating recurring analytical reporting.

Statistical Modeling & Strategic Insights

Conducting cohort analyses, predictive modeling, and identifying trends that drive product, operational, or business efficiency.

Progression Toward Senior / Lead Analytics Partner

Defining data governance standards, leading cross-functional data initiatives, and guiding organizational decision-making with executive stakeholders.

Career Insights Context: Career advancement in data and analytics is driven by quantitative rigor, clear stakeholder communication, and the demonstrated ability to turn raw data into high-leverage business decisions.

Career Insights Editorial Standards

This page provides verified job details sourced from OpenX's recruitment announcement, alongside independent preparation roadmaps authored by the Career Insights editorial team. Career Insights is not affiliated with OpenX and does not collect candidate data or charge application fees.