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.

Key Responsibilities

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

Requirements

Required Skills & Experience

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, backpressure)
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

DevOps & Engineering Practices

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

Tools & Technologies (Preferred Exposure)

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

Key Competencies

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

Desirable Skills

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

What You’ll Bring

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

Benefits

Why Join Us?

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

Data Engineer