Data Engineer – Build Scalable Data Pipelines

About the role

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The role supports analytics, reporting, and AI/ML initiatives by ensuring reliable data access and high data quality.

Key responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Develop and manage data architectures, including data lakes, warehouses, and data marts.
• Ensure data quality, integrity, and consistency across systems.
• Collaborate with data scientists, AI engineers, analysts, and business stakeholders.
• Optimize data pipelines and workflows for performance and cost‑efficiency.
• Implement data governance, security, and compliance best practices.
• Monitor data systems, troubleshoot issues, and ensure high availability.
• Integrate data from multiple sources including APIs, databases, and streaming platforms.
• Maintain documentation for data pipelines, systems, and processes.

Required profile

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
• 5+ years of experience in data engineering or a related role.
• Strong problem‑solving and analytical thinking.
• Attention to detail and data accuracy.
• Effective communication and collaboration skills.
• Ability to work in a fast‑paced, data‑driven environment.
• Continuous learning mindset.

Required skills

• Python
• Java
• Scala
• SQL
• Relational and non‑relational databases
• Apache Spark
• Hadoop
• ETL/ELT tools
• Airflow
• Azure
• AWS
• Google Cloud
• Data modeling and database design
• Data lakes, warehouses, and data marts
• Databricks
• Snowflake, BigQuery, Redshift, Azure Synapse
• Kafka, Kinesis
• Docker
• Kubernetes
• CI/CD pipelines and DevOps practices
• Feature engineering and ML pipeline support