Data Engineer - Marketing & Performance

Codem Inc.

Website: codem.com
Job details:

Company Description

Codem Inc. specializes in scalable, AI-driven eCommerce solutions tailored to transform businesses across industries such as Health & Beauty, Apparel, Consumer Electronics, and Home Goods. With expertise in launching and managing over 100 global B2C and B2B eCommerce platforms, the team draws on experience from industry leaders like Amazon, HP, McKinsey, and more. Operating from offices in San Francisco, Singapore, and Chennai, Codem delivers cost-efficient solutions by utilizing specialized teams and implementing advanced AI technologies. The company helps clients streamline operations, reduce costs, and make data-driven decisions through innovative tools like Augment for AI/ML applications, custom Shopify apps, and efficient DevOps services.

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Role Overview

We are looking for a highly skilled Data Engineer with strong experience in building and maintaining data pipelines for marketing and performance analytics, ideally within an e-commerce environment.

The role focuses on integrating marketing and advertising data sources, building scalable pipelines, and enabling reliable reporting for campaign performance, attribution, and cost analytics.

Key Responsibilities - Data Pipeline Development

Design, build, and maintain robust data pipelines for marketing and performance datasets

Develop and enhance API-based integrations for external data sources

Implement Python-based ingestion and transformation workflows

Data Integration & Processing

Integrate and process data from platforms such as:

Google Ads

Amazon marketing / advertising / marketplace APIs

Handle multiple data sources with inconsistent schemas and API limitations

Optimize incremental data loads and transformation logic

Orchestration & Workflow Management

Build and maintain workflows using:

Apache Airflow

Azure Synapse pipelines (if applicable)

Ensure stable orchestration and scheduling of jobs

Improve pipeline reliability and failure recovery mechanisms

Cloud & Data Platform

Work within Azure cloud environment

Use Spark notebooks for:

Data transformation

Processing workflows

Operational data pipelines

Build and maintain datasets in a data warehouse (DWH) environment

Data Quality & Observability

Implement data quality checks, monitoring, and alerting

Troubleshoot:

Pipeline failures

API issues

Schema changes

Data discrepancies

Improve observability and scalability of data systems

Business Collaboration

Partner with marketing and analytics teams to:

Understand campaign performance requirements

Support attribution and reporting use cases

Build datasets for:

Marketing cost reporting

Campaign performance analysis

 

Required SkillsCore Engineering Skills

Strong experience as a Data Engineer

Advanced Python for:

API integrations

Data processing

Pipeline development

Strong SQL skills

Data Engineering & Architecture

Solid understanding of:

Data warehousing concepts

Data modelling

ETL / ELT design

Tools & Technologies

Apache Airflow

Azure Cloud

Spark / Spark Notebooks

Experience with API-based data ingestion

Marketing Data Experience

Hands-on experience with:

Google Ads APIs

Amazon marketing / marketplace data

Experience building datasets for:

Campaign performance

Marketing cost reporting

Data Operations

Experience with:

Data quality validation

Monitoring & alerting

Troubleshooting production pipelines

Preferred / Ideal Experience

Experience in:

Performance marketing or attribution data engineering

Handling multi-source data pipelines with schema inconsistencies

Optimizing:

Incremental loads

Cost-efficient data processing

Pipeline orchestration reliability

Direct collaboration with marketing / analytics stakeholders

Nice to Have

Experience with retail media / marketplace data ecosystems

Advanced experience with Spark

Understanding of:

Marketing attribution models

Multi-touch attribution logic

Candidate Profile

The ideal candidate is:

Hands-on and technically strong

Proactive in identifying and resolving issues

Focused on pipeline reliability and scalability

Business-aware with understanding of marketing metrics

• Structured and pragmatic in a production environment

Click on Apply to know more.