Job Description:
Data Platform Engineer – Build Scalable Data Systems
The Data Platform Engineer is the architect behind the infrastructure that powers our most critical data-driven initiatives. In this role, you will design, build, and maintain the scalable platforms that support analytics, AI models, media performance tracking, and business intelligence across the consultancy.
You’ll develop and manage cloud-based systems that store, process, and serve large volumes of structured and unstructured data. From real-time data ingestion to batch processing pipelines, your platforms will be the foundation for everything from marketing insights to advanced machine learning applications.
Working closely with data scientists, engineers, and IT teams, you’ll implement solutions such as data lakes, data warehouses, and real-time streaming environments. These systems must be highly available, secure, and optimized for performance — enabling teams to work quickly and with confidence.
Your role also includes maintaining and improving the architecture over time. You’ll evaluate and integrate new technologies, automate workflows, and fine-tune systems for efficiency. Whether deploying infrastructure as code or scaling distributed systems, your work will help ensure our platforms evolve with the business.
Security and governance are central responsibilities. You’ll implement access controls, monitor compliance with data privacy regulations, and support data cataloging and lineage efforts. You’ll contribute to a trusted and compliant data environment that meets both internal and client-facing standards.
You should be comfortable working in cloud ecosystems like AWS, GCP, or Azure, and fluent with tools such as Terraform, Kubernetes, Airflow, Spark, and Kafka. Experience with Snowflake, BigQuery, or Redshift — and familiarity with CI/CD workflows — will be highly valuable.
Strong communication is key. You’ll collaborate across departments, provide technical guidance, and help teams understand how to work effectively with the data platform. Your documentation and onboarding support will also help scale knowledge internally.
The Data Platform Engineer ensures that data is not only stored — but delivered securely, reliably, and efficiently to the people and systems that need it.
This position is essential to enabling real-time insights, powering AI solutions, and creating a high-performing, data-first culture within the consultancy.
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Responsibilities:
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Design and implement data platform architectures.
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Manage and optimize data storage and processing systems.
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Ensure data platform scalability, security, and reliability.
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Collaborate with data scientists and engineers to meet infrastructure needs.
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Deploy and maintain cloud data solutions (AWS, GCP, Azure).
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Monitor system performance and troubleshoot issues.
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Automate platform maintenance and data workflows.
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Support data governance and compliance policies.
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Evaluate and integrate new data platform technologies.
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Document architecture designs and operational procedures.
Preferred Qualifications:
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4+ years experience in data engineering or platform development.
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Expertise in cloud data platforms and services.
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Strong programming skills in Python, Java, or Scala.
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Experience with data warehouse solutions (Redshift, BigQuery, Snowflake).
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Familiarity with streaming technologies (Kafka, Kinesis).
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Understanding of data security best practices.
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Ability to work collaboratively in cross-functional teams.
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Strong problem-solving and system design skills.
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Bachelor’s degree in computer science, engineering, or related field.
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Experience supporting AI and machine learning workloads preferred.
