Forbes Advisor – Data Engineer L2

Forbes Advisor is hiring a skilled and analytical Data Engineer – L2 to support its growing data engineering and marketing analytics ecosystem. As part of the Forbes Marketplace umbrella, Forbes Advisor delivers expert-driven insights, reviews, and financial guidance that help millions of consumers make informed decisions related to personal finance, business, health, and everyday life. This role is ideal for candidates who are passionate about data engineering, Python development, marketing analytics, and cloud-based data processing systems. The position offers the opportunity to work on scalable data pipelines, modern ETL workflows, and performance marketing datasets that directly influence reporting, lead analysis, and digital growth initiatives across the organization.

The Data Engineer – L2 will primarily focus on building and maintaining data ingestion pipelines that process marketing and advertising data from platforms such as Meta Ads and similar digital marketing ecosystems. Candidates will work with APIs, cloud data warehouses, orchestration tools, and large datasets to ensure reliable and accurate delivery of business-critical marketing data. The role involves close collaboration with analytics teams, marketing stakeholders, and senior engineers to support campaign reporting, lead funnel tracking, and operational data workflows. Professionals in this role will gain exposure to modern data engineering practices, cloud-native architectures, workflow automation, and real-world marketing analytics environments.

Working at Forbes Advisor provides employees with an innovation-driven and collaborative environment where technology, analytics, and business strategy intersect. The company emphasizes continuous learning, work-life balance, and employee wellness while offering opportunities to work on impactful data projects that drive business decisions and customer engagement. This role is highly suitable for professionals looking to strengthen expertise in data engineering, API integrations, cloud analytics, ETL development, and AdTech data systems while contributing to one of the leading digital publishing and marketplace platforms.

Roles & Responsibilities

• Build, maintain, and optimize data ingestion pipelines that collect data from APIs, cloud systems, and external marketing platforms.
• Develop efficient Python scripts and SQL queries for data extraction, transformation, validation, and processing activities.
• Support ETL and ELT workflows to ensure accurate, reliable, and timely availability of business and marketing datasets.
• Monitor, troubleshoot, and resolve pipeline failures, performance bottlenecks, and data quality issues across data systems.
• Assist in ingesting and modeling data from Meta Ads and similar advertising platforms for analytics and reporting purposes.
• Create datasets and reporting structures that support campaign performance analysis, lead funnel tracking, and marketing optimization.
• Work with marketing analytics teams to understand campaign structures, ad hierarchies, and key performance metrics such as CTR, CPC, CPA, and conversions.
• Collaborate with business teams, analysts, and engineers to translate business requirements into scalable data solutions and datasets.
• Implement data validation checks and monitoring mechanisms to maintain data integrity, consistency, and operational reliability.
• Maintain technical documentation related to data pipelines, ingestion workflows, datasets, and transformation logic.
• Contribute to performance improvement initiatives and workflow automation processes across data engineering operations.
• Gain deeper understanding of AdTech systems, event tracking, digital marketing analytics, and lead generation ecosystems.

Requirements & Eligibility

• Strong proficiency in Python for data processing, scripting, API integration, and workflow automation tasks.
• Advanced SQL skills with experience writing optimized queries for data extraction, transformation, and reporting.
• Experience building or supporting data ingestion pipelines using APIs and handling pagination, retries, and error management.
• Familiarity with ETL/ELT concepts, workflow orchestration tools such as Apache Airflow, and modern data engineering practices.
• Exposure to cloud-based data warehouses such as BigQuery or similar analytics platforms.
• Basic understanding of Meta Ads platform concepts including campaigns, ad sets, ad-level structures, and conversion tracking.
• Familiarity with marketing performance metrics such as CTR, CPC, CPA, conversions, and lead funnel analytics.
• Strong analytical thinking, debugging capabilities, and problem-solving skills for resolving pipeline and data quality issues.
• Ability to work effectively in cross-functional environments with marketing, analytics, and engineering teams.
• Good communication skills with the ability to explain technical processes, issues, and solutions clearly to stakeholders.
• Exposure to additional marketing platforms such as Google Ads, event tracking tools like GA4, or transformation frameworks such as dbt is preferred.
• Understanding of cloud-native data architectures, business reporting, and scalable data operations will be considered an added advantage.

Expected Salary

For Data Engineer L2 roles at modern analytics and digital technology companies like Forbes Advisor, the estimated salary generally ranges between ₹10 LPA and ₹22 LPA depending on technical expertise, cloud experience, data engineering capabilities, and marketing analytics exposure. Candidates with strong Python, SQL, ETL, and cloud data warehouse experience may receive compensation toward the higher end of the range along with additional wellness benefits, flexible work policies, and long-term career growth opportunities.

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