Data Engineer (Data Platforms & Analytics)

We are looking for a Data Engineer to design, develop, and maintain reliable data infrastructure that supports analytics, digital products, and business decision-making.

In this role, you will work with engineering, product, and analytics teams to transform data from multiple sources into structured, accessible, and scalable datasets. You will be responsible for building data pipelines, improving data quality, and ensuring that our data infrastructure remains reliable as products and workloads grow.

What You’ll Do

• Design, build, and maintain scalable ETL/ELT data pipelines
• Integrate data from APIs, databases, applications, and third-party platforms
• Develop and maintain data models for analytics and reporting
• Work with cloud-based data warehouses and storage solutions
• Monitor pipeline performance, reliability, and data quality
• Identify and resolve bottlenecks in data-processing workflows
• Implement validation and monitoring processes to maintain data consistency
• Collaborate with analysts, developers, product managers, and other technical specialists
• Improve existing data architecture as systems and data volumes scale
• Document data flows, models, dependencies, and technical processes

What We’re Looking For

• 2+ years of experience in Data Engineering, Analytics Engineering, or a similar technical role
• Strong knowledge of SQL
• Experience with Python for data processing and automation
• Practical understanding of ETL/ELT processes and data pipeline architecture
• Experience working with relational databases and data warehouses
• Understanding of data modelling, data quality, and data governance principles
• Experience with cloud environments such as AWS, Google Cloud, or Azure
• Familiarity with Git and modern software development workflows
• Ability to troubleshoot technical issues and work with complex datasets
• Strong analytical thinking and attention to detail

Nice to Have

Experience with tools and technologies such as BigQuery, Snowflake, Redshift, dbt, Airflow, Kafka, or Spark will be an advantage.

Knowledge of BI and analytics platforms, containerization, CI/CD processes, or infrastructure-as-code practices is also valuable, especially when working with larger data ecosystems.

What We Offer

You will join a technology-focused environment where data is treated as a core part of product and business infrastructure. The role provides an opportunity to work with modern data technologies, contribute to architectural decisions, and build systems designed for long-term scalability.

We offer flexible working arrangements, collaboration with experienced specialists across engineering and product teams, opportunities for professional development, and the freedom to propose and implement technical improvements.

If you enjoy turning fragmented data into reliable infrastructure and want to build systems that support real digital products and business decisions, we would be glad to hear from you.

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