🔥 Viewed by 66 students today✓ Verified Listing

Data Engineer - L2

Forbes AdvisorCompetition: Moderate • Entry Level
|Gurugram|Posted 6 days ago|Last verified 6 days ago
✓ Company career page verified✓ Application route verifiedLast checked on Jun 16, 2026
💼 Experience Required
1-3 Years
🕒 Employment Type
Full-time
🎓 Target Batch
2023, 2024, 2025
🚀 Role Category
Data Engineer
📌 How to Apply
Click on the Apply button
💰 Salary
Not publicly disclosed
Compensation follows company standards.
Skills Recommended
PythonSQLdata ingestion from APIsworkflow orchestration toolscloud data warehousesMeta Ads platformmarketing metricslead generation and funnel basics

Company Information

Official Job Details

Job Description

Smart Financial Decisions Made Simple

Data Engineer - L2

Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most.

We are looking for a Data Engineer (L2) with solid experience in Python and data ingestion pipelines, and exposure to digital marketing data, particularly the Meta Ads ecosystem.

In this role, you will contribute to building and maintaining data pipelines that power marketing analytics, campaign reporting, and lead analysis. You will work closely with senior engineers and business teams to support data needs across performance marketing and growth. This role does not involve campaign execution (buying/bidding), but requires a working understanding of ad platforms, marketing metrics, and lead funnels.

Responsibilities

Data Engineering & Pipelines

· Build and maintain data ingestion pipelines from APIs and other data sources

· Write efficient Python and SQL for data transformation and processing

· Support ETL/ELT workflows, microservices and ensure timely data availability

· Troubleshoot pipeline failures and assist in performance improvements

Marketing Data Support

· Assist in ingestion and modeling of data from Meta Ads and similar platforms

· Help create datasets for:

o Campaign performance reporting

o Lead funnel tracking

· Develop familiarity with:

o Campaign structure (campaign/ad set/ad level)

o Basic performance metrics (CTR, CPC, CPA)

o Conversion tracking concepts

Business Collaboration

· Work with marketing and analytics teams to understand data requirements

· Support analysis related to lead quality and campaign performance

· Help translate business needs into data queries and datasets

Data Quality & Maintenance

· Implement basic data validation checks

· Monitor pipelines and resolve data issues

· Maintain documentation for pipelines and datasets

· Required Skills & Qualifications

· Core Technical Skills

· Proficiency in Python (data processing, API handling)

· Strong SQL skills

· Experience with data ingestion from APIs (basic handling of pagination, retries)

· Familiarity with workflow orchestration tools (e.g., Airflow or similar)

· Exposure to cloud data warehouses (BigQuery, etc.)

Ad Platform Exposure

· Basic understanding of Meta Ads platform concepts

· Familiarity with:

· Marketing metrics (CTR, CPC, conversions)

· Lead generation and funnel basics

· Willingness to learn deeper AdTech concepts

Soft Skills

· Good problem-solving and debugging skills

· Ability to work in a collaborative, cross-functional environment

· Clear communication of technical work and issues

Good to Have

· Exposure to other marketing platforms (Google Ads, etc.)

· Experience with tools like dbt or similar transformation frameworks

· Understanding of event tracking (GA4, etc.)

What Success Looks Like

· Reliable execution of data pipelines with minimal supervision

· Accurate and timely delivery of marketing datasets

· Growing understanding of marketing data and business use cases

· Effective collaboration with senior engineers and stakeholders

Perks:

● Day off on the 3rd Friday of every month (one long weekend each month)

● Monthly Wellness Reimbursement Program to promote health well-being

● Monthly Office Commutation Reimbursement Program

● Paid paternity and maternity leaves

💡 Editor's Career Guide for this Role

🎯 Why This Role Matters

This role provides direct hands-on experience with production-grade codebases, agile development lifecycles, and scalable architectures. It serves as a major accelerator for careers in backend, frontend, or full-stack software development.

⚡ Key Skills Needed

To stand out for this position, hiring managers for this Data Engineer - L2 role are looking for:

  • Strong foundational knowledge in core engineering principles.
  • Ability to adapt quickly to the fast-paced environment at Forbes Advisor.
  • Proficiency in Python, SQL, data ingestion from APIs.

💡 Application Tips

  • Tailor your resume: Highlight specific projects or experiences that align directly with current initiatives at Forbes Advisor.
  • Prepare for behavioral rounds: Be ready to discuss times you have handled failure, tight deadlines, or team conflicts.
  • Leverage the AI Assistant: Use the AI Assistant button above to evaluate your resume against this specific Data Engineer - L2 description before applying.

CampusToCareer Analysis

⭐ Original AnalysisLast Verified: Jun 16, 2026

🎯 Should You Apply?

✓ Suitable for:

  • Business graduates
  • Engineering students
  • Students interested in consulting or analytics

✗ Not ideal if:

  • Looking strictly for software development/coding roles
  • Uncomfortable with stakeholder presentations

⚡ Difficulty Level

Application DifficultyMedium
Expected CompetitionHigh
Interview Rounds2–4 rounds
Note: These stats are evaluated by our editorial team based on past application metrics and hiring trends.

🎓 What You Will Learn

Skills you may develop through this role:

  • Python
  • SQL
  • data ingestion from APIs
  • SQL database query optimization

📝 How to Prepare

  1. Master SQL basics (joins, subqueries, group by, window functions)
  2. Understand business analysis lifecycles and requirement gathering
  3. Practice communication and case study problems
  4. Learn key metrics (conversion, churn, retention) used in analysis

📄 Resume Match Tips

Highlight these on your resume to stand out:

  • Highlight communication projects and business case studies
  • List SQL and Excel proficiency with concrete project examples
  • Showcase leadership, clubs, or team collaboration experiences
⚠️

Reality Check

This role is less technical and more communication-oriented. Students expecting software development or compiler work may find the role different from expectations.

❓ Frequently Asked Questions

Editorial Analysis Disclaimer: The opinions expressed in this CampusToCareer Analysis are formulated by our platform editors to guide students. Please review the official company listing before applying.
Apply Now
Candidate Guide • 5 min role analysis

More than a copied JD: use this page to prepare before you apply.

Forbes Advisor is hiring for Data Engineer - L2 in Gurugram. This page goes beyond the raw listing so students can understand what the role usually expects, how to prepare for screening, and how to apply more thoughtfully instead of forwarding a resume blindly.

Application Difficulty: MediumCompetition: HighPreparation Time: 3–5 Days

⚡ Quick Preparation Snapshot

Role Fit:
7/10
Competition:
High
Interview Difficulty:
Medium
Freshers Friendly:
Yes
Remote:
No
Recommended:
2023, 2024, 2025 Batch

🏢 Why Students Consider Forbes Advisor

✓ Advantages

  • Direct impact on product & business decisions
  • Cross-functional visibility across departments
  • Stepping stone to Data Science & ML tracks
  • Data-driven problem-solving exposure

⚠ Potential Challenges

  • Ad-hoc SQL report extraction requests
  • Manual cleaning of messy dataset pipelines

⚙️ Role Context & Recruiter Lens

Data Engineer - L2 is likely not just a keyword match. In real hiring, titles compress multiple operational expectations. You should read this listing as a signal of day-to-day team coordination and troubleshooting.

✓ What Recruiters Typically Evaluate

  • Advanced SQL queries (joins, windowing)
  • Analytical business metrics (churn, conversion)
  • Data visualization tool skills (PowerBI/Tableau)
  • Structured logical breakdown of case studies
  • Storytelling with quantitative numbers

❌ Common Mistakes Students Make

  • Applying with a generic resume that does not align with recommended skills.
  • Ignoring basic company research before the screening interview.
  • Using broken or inactive GitHub and portfolio showcase links.
  • Listing complex projects on the resume without being able to explain details.
  • Clicking apply without verifying batch eligibility or graduation cutoffs.

📅 30-Day Preparation Roadmap

Week 1: Advanced SQL Query Drills

Practice aggregation, subqueries, CTEs, and window functions on SQL platforms.

Week 2: Interactive Dashboard Build

Set up Tableau/PowerBI visual displays of public datasets to highlight trends.

Week 3: Business Metrics Analysis

Study indicators like user retention, conversion rates, and profit margin analysis.

Week 4: Case Study & Presentations

Practice explaining analytics trends simply to simulated business clients.

📈 Typical Hiring Journey Timeline

1. Application
Initial profile submission
2. Shortlisting
Recruiter resume screening
3. Assessment
Aptitude/coding test assessment
4. Interview
Technical & HR conversation rounds
5. Offer
Letter of intent & onboarding

Recommended Guides

✍️ Reviewed by: CampusToCareer Editorial Team📅 Last Updated: 13 June 2026✓ Fact Check Status: Verified