Data Engineer

Role Overview

We are seeking a skilled and motivated Data Engineer with 2+ years of experience to design, build, and maintain scalable data pipelines and systems. You will play a key role in developing both batch and real-time data processing solutions, working with modern data technologies and cloud platforms. This role requires strong engineering fundamentals, a passion for data, and the ability to work collaboratively in Agile teams.

• Design, build, and maintain scalable ETL/ELT and streaming data pipelines
• Develop robust and efficient data processing solutions using Java (preferred) or Python
• Implement and manage stream processing systems using tools like Kafka, Flink, or Spark
• Work with large-scale distributed systems, ensuring performance, scalability, and reliability
• Collaborate with cross-functional teams to deliver high-quality data solutions
• Apply software engineering best practices including testing, version control, and CI/CD
• Contribute to architecture discussions and help improve data platform capabilities
• Monitor, troubleshoot, and optimize data pipelines and systems
• Maintain clear documentation for data pipelines, systems, and processes

• 2+ years of experience in data engineering or large-scale data systems
• Strong programming skills in Java (preferred) or Python
• Hands-on experience with at least one:
  Kafka, Flink, or Spark (Kafka/Flink preferred)
• Solid understanding of stream processing concepts (event time, state, back pressure)
• Experience building ETL/ELT pipelines or real-time streaming workflows
• Knowledge of distributed systems and microservices architecture
• Experience with cloud platforms (AWS preferred, Azure/GCP also acceptable)
• Good understanding of data processing performance and scalability considerations
• Familiarity with Git, CI/CD pipelines, and software engineering best practices

• Experience using CI/CD tools (e.g., Azure Dev Ops, Git Hub Actions, Jenkins)
• Infrastructure-as-Code experience (
  Terraform preferred
  )
• Familiarity with containerisation (Docker) and orchestration (
  Kubernetes/EKS
  )

• Experience with modern data platforms such as Databricks, Snowflake, or Big Query
• Exposure to cloud-native data services and data lake/warehouse solutions

• Strong analytical and problem-solving skills
• Ability to work effectively in Agile delivery environments
• Excellent communication skills with both technical and non-technical stakeholders
• Proactive mindset with a focus on continuous improvement

• Experience in client-facing or consulting roles
• Exposure to real-time, low-latency systems
• Cloud or data engineering certifications (
  AWS, Azure, GCP
  )
• Experience mentoring or supporting junior team members

• Passion for building scalable, high-performance data systems
• Strong engineering mindset and attention to detail
• Collaborative approach and willingness to learn and grow

• Dedicated support: Ongoing mentoring and guidance from experienced professionals
• Upskilling opportunities: Training and development to further strengthen your skillset
• Career growth: Work on impactful projects and progress into more senior roles
• Collaborative culture: A team environment that values knowledge sharing and continuous improvement
• Competitive salary and benefits package