Data Engineer

About the Role:We are looking for a highly capable Data Engineer to design and build scalable data infrastructure and analytics systems from the ground up. This role will play a key part in establishing the company’s data foundation to support large-scale data processing, performance tracking, and analytics. Candidates with prior experience in advertising, marketing, or Internet platforms will be well-suited, as the role involves working with high-volume, multi-source user and campaign data.Key Responsibilities:Design, develop, and deploy end-to-end data infrastructure and pipelines to process, integrate, and analyse data from diverse digital sources.Build and optimise ETL/ELT workflows for marketing, advertising, and user behavioural data.Architect scalable data warehouses and data lakes to support analytics, attribution modelling, and performance reporting.Collaborate with data analysts, data scientists, and business stakeholders to define data requirements and deliver actionable datasets.Implement data quality, governance, and security frameworks to ensure integrity and compliance across platforms.Optimise storage and compute resources for high-performance querying and cost efficiency.Evaluate and integrate new data tools and technologies to support evolving business needs.Establish monitoring and alerting systems to ensure data reliability and system uptime.Document data models, flows, and infrastructure design for long-term maintainability.Qualifications & Requirements:Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.5+ years of experience in data engineering, with proven success in building or scaling data infrastructure from scratch.Industry experience in digital advertising, marketing analytics, or large-scale internet platforms is required.Proficiency in SQL and a programming language such as Python, Scala, or Java.Strong hands-on experience with data pipeline orchestration tools (e.g., Airflow, Prefect, Dagster).Proficiency with data warehousing technologies (e.g., Snowflake, BigQuery, Redshift) and data lake architectures (e.g., S3, Delta Lake).Familiarity with big data and streaming technologies such as Spark, Flink, or Kafka.Experience working with marketing data sources and APIs (e.g., Google Ads, Meta Ads, TikTok, DSPs, or analytics platforms).Solid understanding of data modelling, attribution, and campaign performance tracking.Experience with cloud environments (AWS, GCP, or Azure) and infrastructure automation tools.Strong analytical mindset with the ability to design scalable and maintainable data solutions.Excellent communication and collaboration skills across technical and business teams.