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Marketing Data Engineer| Hybrid

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Hybrid

Marketing Data Engineer| Hybrid

Lexmark Research & Development Corporation

Marketing Data Engineer| Hybrid

Skills

Google Cloud PlatformSQL QueriesPythonpandasDatabricksData AnalysisAIAWSCommunication CampaignSalesforcePySparkAdobe AnalyticsComplianceAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Cebu City, 6000 Cebu, Philippines

Work mode:

Hybrid

Published on:

21 August 2026

What they need


Lexmark is now a proud part of Xerox, bringing together two trusted names and decades of expertise into a bold and shared vision.

When you join us, you step into a technology ecosystem where your ideas, skills, and ambition can shape what comes next. Whether you’re just starting out or leading at the highest levels, this is a place to grow, stretch, and make real impact—across industries, countries, and careers.

From engineering and product to digital services and customer experience, you’ll help connect data, devices, and people in smarter, faster ways. This is meaningful, connected work—on a global stage, with the backing of a company built for the future, and a robust benefits package designed to support your growth, well-being, and life beyond work.

JOB SUMMARY:

The Marketing Data Engineer role is part of the Marketing Data Strategy and AI Compliance team. The role will support data-driven decision-making across sales and marketing organizations, and focuses on querying, transforming, and preparing data from enterprise data platforms (e.g., Databricks/data lake) to enable intelligent audience segmentation, data aggregation and attribution across multiple data sources, and performance insights based on marketing campaign efforts to the identified audiences.

This Marketing Data Engineer partners closely with IT and Data Governance teams for required access and permissions but does not own underlying data infrastructure or platform management.

KEY ROLES & RESPONSIBILITIES:

  • Write and optimize SQL and/or Python code to extract, transform, and analyze data from the marketing data lake

  • Build and maintain marketing-ready datasets for segmentation, attributed marketing activities, and campaign/audience analysis

  • Support ingestion and preparation of data into the marketing data lake within the confined and format approved and governed by the IT and data governance teams

  • Develop reusable queries, scripts, and pipelines to improve efficiency and consistency of analysis

  • Partner with marketing stakeholders to translate business questions into data solutions

  • Ensure data quality, consistency, and proper documentation of datasets and logic

  • Support integration of data across relevant sales and marketing platforms (e.g., Salesforce, Eloqua, Adobe Analytics, display advertising networks, social media platforms, etc.)

  • Leverage AI tools to facilitate operational efficiency and speed of execution, such as Claude, Writer.ai, Microsoft Fabric, etc.

COMPETENCIES, SKILLS, KNOWLEDGE & ABILITIES:

  • Working knowledge of Python for data manipulation and analysis (e.g., pandas, PySpark)

  • Strong proficiency in SQL, including complex joins, aggregations, and query optimization

  • Experience working with large-scale datasets in cloud data platforms (e.g., AWS, Azure, GCP)

  • Solid understanding of marketing data structures and concepts, including campaigns, leads, funnels, and attribution models

  • Ability to interpret marketing performance metrics and translate them into actionable insights

  • Proven ability to translate business requirements into technical queries and data solutions

  • Strong analytical thinking with attention to detail and data accuracy

  • Ability to work cross-functionally with marketing, analytics, and technical teams

  • Effective communication skills to explain data insights to non-technical stakeholders RESPONSIBILITIES

EDUCATION, EXPERIENCE & CERTIFICATIONS, BASIC REQUIREMENTS:

  • Bachelor’s degree in Data Analytics, Computer Science, Information Technology, Marketing Analytics, or a related field (or equivalent practical experience)

  • Minimum 3 years’ working experience in a business environment

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