Data Engineer

About the role

We are looking for a skilled Data Engineer to build, optimize, and maintain scalable data infrastructure that powers analytics, AI, and machine learning products. The role involves designing robust data pipelines, integrating data from multiple sources, and ensuring data quality and accessibility across the organization. You will collaborate closely with software engineers, data scientists, and product teams.

Key responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and manage modern data warehouses and data lakes.
• Develop reliable batch and real‑time data processing pipelines.
• Integrate data from APIs, databases, third‑party platforms, and cloud services.
• Ensure high standards of data quality, integrity, security, and governance.
• Optimize data models and database performance for analytics and reporting.
• Monitor, troubleshoot, and improve data pipeline reliability and performance.
• Collaborate with Data Scientists, ML Engineers, Product Managers, and Software Engineers to deliver data solutions.
• Implement CI/CD practices and infrastructure automation for data workflows.
• Document data architecture, pipeline designs, and engineering best practices.

Required profile

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field.
• 4+ years of experience in Data Engineering or Backend/Data Platform development.
• Strong proficiency in Python and SQL.
• Experience building ETL/ELT pipelines using orchestration tools such as Airflow, Prefect, or Dagster.
• Knowledge of relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, Cassandra).
• Hands‑on experience with cloud platforms (AWS, Azure, Google Cloud Platform) and cloud data warehouses (Snowflake, BigQuery, Amazon Redshift, Azure Synapse).
• Experience with distributed processing frameworks like Apache Spark.
• Familiarity with message streaming technologies such as Kafka or RabbitMQ.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Proficiency with Git and collaborative software development workflows.

Required skills

• Python
• SQL
• Airflow
• Prefect
• Dagster
• PostgreSQL
• MySQL
• MongoDB
• Cassandra
• AWS
• Azure
• Google Cloud Platform
• Snowflake
• BigQuery
• Amazon Redshift
• Azure Synapse
• Apache Spark
• Kafka
• RabbitMQ
• Docker
• Kubernetes
• CI/CD pipelines
• Git
• dbt
• Delta Lake
• Apache Iceberg
• Apache Hudi
• Terraform