Data Engineer - DTC

The Data Engineer will design, develop, and maintain scalable data pipelines and systems to support the company's direct-to-consumer (DTC) strategy. This role will collaborate with cross-functional teams such as marketing, eCommerce, supply chain, and finance to ensure data is accessible, accurate, and ready for analytics and business insights.

Key Responsibilities:

1. Data Pipeline Development:
• Design, build, and maintain ETL (Extract, Transform, Load) pipelines to gather data from various sources such as eCommerce platforms, customer relationship management (CRM) systems, and marketing tools.
• Optimize pipelines for performance, ensuring minimal downtime and smooth data flow.
2. Data Integration:
• Integrate data from multiple sources, including websites, mobile apps, inventory systems, and customer feedback tools, into centralized data warehouses.
• Work closely with Data Scientists and Analysts to support data needs for marketing optimization, personalization, and customer journey analysis.
3. Database Management:
• Develop and maintain databases (SQL/NoSQL) and data warehouses (e.g., Redshift, Snowflake) to store structured and unstructured data.
• Implement indexing, partitioning, and data schema management for efficient querying and retrieval.
4. Data Quality and Governance:
• Ensure high data quality through monitoring, validation, and error checking.
• Develop data governance policies to maintain data security, privacy (GDPR, CCPA), and integrity.
5. Collaboration with Business Units:
• Work closely with stakeholders to understand business requirements and translate them into technical solutions.
• Collaborate with marketing, eCommerce, and product teams to implement data solutions that drive business objectives like customer segmentation, churn prediction, and supply chain optimization.
6. Technology and Tooling:
• Utilize big data tools such as Spark, Hadoop, and Kafka to process large datasets.
• Develop APIs and real-time data streaming solutions to support real-time analytics and decision-making.
• Automate data flows and ensure scalability.

Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Data Science, or related field.
• 3+ years of experience in data engineering, with a focus on consumer data or DTC business models.
• Experience with ETL tools (e.g., Talend, Apache NiFi) and workflow management platforms (e.g., Airflow).
• Proficiency in SQL, Python, and Scala.
• Experience with cloud platforms such as AWS (S3, Redshift, EC2), Google Cloud (BigQuery), or Azure.
• Familiarity with data warehousing solutions like Snowflake or Redshift.

Preferred Skills:

• Experience in consumer goods, eCommerce, or retail industries.
• Knowledge of digital marketing tools such as Google Analytics, Shopify, or Salesforce Marketing Cloud.
• Experience with A/B testing and customer journey analysis.
• Familiarity with GDPR and CCPA compliance for data privacy.

Key Competencies:

• Problem-solving and critical thinking.
• Strong communication skills to work with non-technical stakeholders.
• Ability to manage multiple projects and deadlines.