Data Engineer at Zebra Technologies
At Zebra Technologies, we are a community of innovators creating new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs.
Role Overview
Company Overview
At Zebra Technologies, we are a community of innovators creating new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs.
Role Overview
As a Data Engineer I (Power BI Developer & Administrator), you will transform raw data into actionable business intelligence. This role requires a balance of analytical insight, technical proficiency in data modeling/DAX, and managing the Power BI service environment.
Candidate Guidelines
Applicants should have 1-2 years of hands-on experience in Power BI development, data administration, and writing SQL queries across cloud data warehouses. Candidate interactions will strictly occur via @zebra.com email addresses.
Eligibility Criteria & Qualifications
- 1 to 2 years of hands-on professional experience building and administering Power BI environments.
- Strong proficiency in writing and optimizing SQL queries (joins, aggregations, subqueries).
- Experience connecting to and querying modern cloud platforms like Snowflake, Databricks, Azure SQL, BigQuery, or Redshift.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related quantitative discipline.
Key Responsibilities
Data Preparation & Quality
- •Translate logical business requirements into clear technical specifications and analytical workflows.
- •Configure and manage Power BI service environments, Row-Level Security (RLS), workspaces, deployment pipelines, and data gateways.
Analysis, Reporting & Visualization
- •Connect directly to backend enterprise systems (SQL databases, cloud warehouses, APIs) and design optimized data schemas (Star/Snowflake).
- •Monitor report performance, troubleshoot dataset refresh errors, and build visually clear dashboards.
Insights & Stakeholder Communication
- •Author high-performing DAX queries, calculations, and measures, while executing data cleansing in Power Query.
Required Skills & Technologies
How to Apply
Submit your application directly through Zebra Technologies'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 Zebra Technologies's direct careers page.
Complete and submit your application directly on the employer's portal.
You will be directed to Zebra Technologies's official careers portal. Career Insights does not process applications or charge any candidate fees.
The specifications above are verified official details published by Zebra Technologies. Candidates should verify all final terms, deadlines, and eligibility directly on Zebra Technologies's official careers portal before submitting an application.
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.
B.E / B.Tech / MCA / B.Sc
Hiring evaluations prioritize demonstrable problem-solving, domain competence, and practical project evidence over specific degree pedigree.
Proficiency in relational databases, SQL queries, and data extraction.
Master complex SQL operations: Window functions (ROW_NUMBER, RANK, DENSE_RANK), CTEs, multi-table JOINs, and query execution plan analysis.
Data cleaning, transformation, and reporting dashboards.
Be prepared to clean messy datasets using Python (Pandas/NumPy) or Excel, identify statistical outliers, and explain KPI metric definitions.
Familiarity with databases, schema modeling, and structured query writing.
Be prepared to explain relational normalization (1NF-3NF), indexing trade-offs, foreign key constraints, and transactional consistency.
Familiarity with Git branching, pull requests, and collaborative repository management.
Review Git branch workflows, pull request code reviews, and maintain clean commit history with descriptive messages.
Onsite (Bengaluru, Karnataka) operational structure.
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
- 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
Topic 2: Data Cleaning, Wrangling & Validation
- 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
Topic 3: Metric Definition, KPI Modeling & Dashboard Architecture
- Designing intuitive business dashboards (Power BI, Tableau, Looker)
- Formulating unambiguous metric definitions (retention, churn, cohort LTV)
- Choosing appropriate data visualizations for business decision-making
Topic 4: Business Problem Solving with Data & Hypothesis Testing
- Formulating testable hypotheses from operational questions
- Segmenting customer or operational cohorts to isolate drivers
- Translating statistical patterns into concrete operational recommendations
Topic 5: Cross-Functional Storytelling & Analytical Communication
- 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
* 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 Zebra Technologies.
Practical Project
Turn the listed data skills into a portfolio exercise using a realistic dataset, analysis workflow, and decision-focused output.
Customer Cohort Retention & Churn Analyzer
A SQL-driven analytics project that calculates monthly cohort retention, customer lifetime value, and churn indicators from raw transaction tables.
Advanced SQL (Window Functions, CTEs), Data Modeling, Business Intelligence Visualization, Statistical Analysis
Include database schema diagrams, reproducible sample data generation scripts, and screenshots of key cohort insights charts.
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 Zebra Technologies.
Before You Apply
Verify your dataset portfolios, dashboard presentations, and application materials before applying.
Ensure your resume highlights SQL queries, data manipulation projects, and interactive dashboard links involving Power BI, DAX, SQL.
Confirm that your degree, graduation year (Not specified), and location match Zebra Technologies's criteria.
Have 1–2 data analysis projects prepared. Be ready to explain your data cleaning methodology, SQL aggregation queries, and actionable conclusions.
Submit your application directly through Zebra Technologies'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.
This page provides verified job details sourced from Zebra Technologies's recruitment announcement, alongside independent preparation roadmaps authored by the Career Insights editorial team. Career Insights is not affiliated with Zebra Technologies and does not collect candidate data or charge application fees.
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