Data Engineer

About the role

Our client, a leading IT company, is looking for a mid‑senior level Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that support analytics, AI initiatives, and enterprise‑wide data solutions across cloud and on‑premise environments.

Key responsibilities

• Develop and operate robust ETL/ELT pipelines and distributed data processing workflows.
• Manage data warehouses, data lakes, and streaming platforms ensuring performance, scalability, and reliability.
• Integrate and transform data from APIs, databases, flat files, and real‑time streaming sources.
• Implement data governance, validation, monitoring, and security best practices.
• Collaborate with data scientists, ML engineers, and business teams to deliver reliable, accessible datasets.

Required profile

• Minimum 5 years of experience in data engineering or large‑scale backend data systems.
• Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, or a related field.
• Strong analytical thinking, troubleshooting abilities, and high attention to detail.
• Excellent communication and collaboration skills in fast‑paced, cross‑functional environments.

Required skills

• Apache Spark, Hadoop, Flink
• SQL and NoSQL databases
• Data‑warehousing solutions such as Snowflake or BigQuery
• Python, Bash scripting, ETL/ELT development, API‑based integrations
• Kafka, Kinesis
• CI/CD pipelines and DevOps practices