Data Engineer

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Our client is a leader in personalized customer experiences. The company is a world-leading Centre of Excellence that helps businesses humanize the relationship between the brand and the customer through hyper-personalization at scale, marketing automation, and CRM. With the brain of a consultancy, the heart of an agency, and the power of technology and data, they work with some of the world’s most admired brands on their transformation journey to becoming truly customer-centric. Together, they are 1000+ technology specialists, data scientists, strategic thinkers, consultants, operations experts, and creative minds from 55+ nationalities.

Key Responsibities

• Identify, collect, and integrate data from various sources by building high-quality data pipelines and data models for analytics and business intelligence (BI) purposes.
• Develop and optimize code to enable pipelines at minimum cost and ease of maintenance.
• Build monitoring procedures & tools to ensure solid ETL flows and data quality.
• Design processes and tools to correct ETL incidents.
• Collaborate with CRM developers, data scientists, data analysts, and product owners to ensure the supplied data supports the business initiatives.
• Consult our data analytics teams to ensure best practices on the technical use of data are followed.
• Design data architectures and collaborate in data migrations in cloud environments.

Required Qualifications

• Experience in data engineering, big data, business intelligence, or data science.
• Experience in Spark, Python, Scala, or similar.
• Excellent SQL skills enabling large-scale data transformation and analysis.
• A comprehensive understanding of cloud data warehousing, data pipelines and data transformation (extract, transform, and load) processes and supporting technologies such as Google Dataflow, Looker, DBT, EMR, CI/CD Pipelines, Airflow DAGs, and other analytics tools.
• Experience with cloud-based data infrastructures (Ideally GCP, but AWS or Azure would also suffice)
• Programming experience in Javascript, Python, or similar.
• Expertise in managing databases, including performance tuning, backup, and recovery.
• Solid knowledge of data quality management best practices, including data profiling, data cleansing, and data validation
• Knowledge of strengths and limitations of visualization tools (e.g. PowerBI, Tableau, Looker, etc.) in terms of data modeling in the visualization tools.
• Understanding of versioning control tools like GitHub to changes related to dbt models and transformations, ensuring that changes are tracked, documented, and reviewed by the appropriate stakeholders.
• Knowledge of applying data governance principles, policies, and practices that ensure data accuracy, consistency, and security.
• Knowledge of Kubernetes would be an advantage.

Nice-to-Have Skills

• Strong desire to contribute towards keeping data tidy and well-organized.
• Ability to think critically, identify issues autonomously, and propose corrective actions.
• Build great relationships with your team and stakeholders.

Upon further discussion with our client.