Key skills
AirflowAWSCloudETLIoTJavaKafkaPythonScalaSparkSQLTableauTensorflowAIMachine LearningMLTensorFlowMLOpsELTData EngineeringAnalyticsLookerBISnowflakeDatabricksLambdaS3GlueAthenaSageMakerKinesisSaaS
About this role
Role Overview
- architecture and maintain cutting-edge data systems that power analytics, AI, and operational decision-making.
- take ownership of end-to-end data lifecycles, designing pipelines, models, and architectures that support real-time insights and machine learning at scale.
- Build modern, cloud-native data platforms (AWS, Snowflake, Databricks) supporting batch and streaming use cases.
- Automate ETL/ELT workflows, optimise data models, and enable self-serve analytics and AI.
- Manage ingestion, storage, processing, and delivery of structured and unstructured data.
- Continuously tune infrastructure for high concurrency, low latency, and cost efficiency.
- Ingest telemetry, API, and application data in real time to power dashboards and AI-driven tools.
- Provision datasets for ML/AI workloads, integrating with SageMaker, Snowflake ML, and MLOps best practices.
- Ensure robust data governance, compliance (GDPR, SOC 2), and enterprise-grade security.
- Work closely with Product, Engineering, DevOps, and Analytics teams to align data solutions with business goals.
Requirements
- significant experience in technology roles, with 5+ years in data engineering on real-time, scalable cloud platforms (AWS & Snowflake preferred).
- Experience in SaaS/product companies managing large-scale IoT, telemetry, or digital datasets is highly desirable.
- AWS (S3, Glue, Lambda, Athena, Kinesis)
- Snowflake (data pipelines, schema design, query optimization)
- Data modeling, ETL/ELT, real-time streaming (Kafka, Kinesis)
- Big data processing (Spark, Airflow), SQL, Python, Java/Scala
- BI & analytics platforms (Tableau, Looker)
- ML/AI integration (SageMaker, TensorFlow, Snowflake ML, feature stores)
- Data governance, security, and compliance frameworks.
- Qualifications Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field (Master’s preferred)
- Relevant certifications (AWS Certified Data Analytics, Solutions Architect, SnowPro Core)
Tech Stack
- Airflow
- AWS
- Cloud
- ETL
- IoT
- Java
- Kafka
- Python
- Scala
- Spark
- SQL
- Tableau
- Tensorflow
Benefits
- Competitive compensation
- A base salary that reflects your expertise and impact.
- Bonus scheme to share in our success.
- Flexibility & work-life balance
- Remote working arrangements to support your lifestyle.
- An open holiday policy with no upper limit—take the time you need, when you need it.
- Support for volunteering and causes that matter to you.
- Opportunities for professional development and career progression.
- Exposure and interaction with global teams.
- A commitment to diversity, equity, and inclusion.
- A collaborative environment where your voice is valued and your wellbeing is prioritised.
- The chance to work on technology that drives global economic inclusion and makes a real difference in people’s lives.