Overview:

A global consumer goods company is looking for a Senior Data Engineer – Digital Analytics & Insights Infrastructure to design, build, and optimize scalable data solutions that support digital analytics and business intelligence efforts. This role is essential for enabling data-driven decision-making by delivering reliable pipelines, cloud-based infrastructure, and actionable insights across marketing and customer behavior analytics. The ideal candidate is a technically strong data engineer with a passion for building high-quality, resilient systems that power modern analytics capabilities.

Key Responsibilities:

• Pipeline Development: Design and build robust, scalable data pipelines using tools such as dbt, and manage data ingestion, transformation, and processing on cloud platforms like Google Cloud, AWS, or Azure.
• Data Modeling: Create and maintain well-structured data models and schemas to support marketing analytics, ensuring quality, consistency, and usability across teams.
• ETL Workflows: Build and maintain ETL processes to move and prepare data from diverse sources, such as web analytics, CRM systems, and marketing platforms, into centralized storage environments.
• BI Integration: Integrate data systems with visualization and business intelligence tools (e.g., Looker, Power BI, Tableau) to support self-service analytics for marketing and digital teams.
• Performance Optimization: Monitor data pipeline performance and optimize data flows and queries to ensure responsive and reliable reporting.
• Data Quality & Governance: Implement rigorous data validation, quality checks, and contribute to governance frameworks to ensure trusted data delivery.
• Stakeholder Collaboration: Partner with analysts, data scientists, and business units to gather requirements and develop technical solutions that meet evolving analytics needs.
• Innovation: Research and evaluate new data engineering tools and practices, proposing improvements that enhance system performance and insight generation.

Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• 4-5 years of hands-on experience in data engineering, preferably in support of marketing or digital analytics.
• Proficient in developing and orchestrating data workflows using tools like dbt or Airflow.
• Strong skills in SQL and modern data modeling techniques.
• Experience with cloud data services such as BigQuery, Snowflake, or Redshift.
• Familiarity with Google Analytics, CRM data, and other digital marketing data sources.
• Advanced experience using BI tools like Looker, Power BI, or Tableau.
• Working knowledge of Python or another scripting language.
• Strong analytical thinking and communication skills.
• Experience with Agile teams and cross-functional collaboration.