Data Engineer

We’re looking for a Data Engineer who’s passionate about building reliable, scalable, and cost-efficient data systems. You’ll work with a modern stack — Kafka, Google Cloud Platform (GCP), AWS — to design and maintain the pipelines that power analytics, machine learning, and product insights. This is an IC2-level role, ideal for someone with solid foundational skills in data engineering who’s ready to deepen their expertise, take ownership of workflows, and collaborate across teams.

What’s On Your Plate?

• Design, build, and maintain data pipelines and workflows for batch and streaming use cases.
• Work with Kafka to manage real-time data ingestion and event-driven architectures.
• Leverage GCP and AWS services for storage, processing, and orchestration (e.g., BigQuery, Dataflow, S3, Lambda).
• Orchestrate workflows using tools like Airflow or similar schedulers.
• Ensure data quality and reliability through monitoring, alerting, and automated validation.
• Collaborate with analysts, data scientists, and product teams to understand requirements and deliver data solutions that drive business impact.
• Optimize for cost and performance across cloud environments.
• Participate in code reviews, documentation, and knowledge sharing to raise the bar for the team.

What Did We Order?
What We’re Looking For

• Experience (1–3 years) in data engineering, software engineering, or a related field.
• Proficiency in SQL and at least one programming language (Python preferred).
• Understanding of data modeling, ETL/ELT concepts, and cloud-based data warehouses.
• Familiarity with streaming platforms (Kafka, Kinesis, or similar).
• Comfort working in cloud environments (GCP, AWS, or Azure).
• Strong communication skills — able to explain technical concepts to non-technical audiences.
• Growth mindset — eager to learn, adapt, and take on new challenges.

Nice-to-Have (But Not Required and willing to learn)

• Experience with infrastructure-as-code (Terraform, CloudFormation).
• Exposure to containerization (Docker, Kubernetes).
• Knowledge of data governance, security, and compliance best practices.