Data Engineer

About the Role

We are looking for a skilled Data Engineer with experience in big data technologies to join our dynamic team. In this role, you will design, build, and maintain scalable data pipelines and infrastructure that support analytics, machine learning, and business intelligence. You will work with large datasets, cloud platforms, and modern data engineering tools to ensure our data is accessible, reliable, and optimized for performance. You will collaborate closely with data scientists, analysts, and other engineers to develop solutions that enable data-driven decision-making across the organization.

Key Responsibilities

• Design, build, and maintain ETL/ELT pipelines for batch and streaming data.
• Work with big data processing tools such as Apache Spark or PySpark for large-scale transformations.
• Manage and optimize data storage in data lakes, warehouses, or lakehouse architectures.
• Ingest data from APIs, logs, IoT devices, and cloud storage (S3, GCS, etc.).
• Implement data quality checks, monitoring, and governance practices.
• Collaborate with cross-functional teams to deliver data solutions.
• Automate workflows using tools like Airflow, dbt, or MageAI.
• Document data processes, architecture, and best practices.

• 2+ years of experience in data engineering or a related field.
• Proficiency in Python, SQL, and working with large datasets.
• Experience with cloud platforms such as AWS (S3, Glue, Athena, EMR, Redshift).
• Understanding of data modeling and warehousing concepts (star/snowflake).
• Familiarity with big data frameworks (Spark, PySpark) and orchestration tools (Airflow, dbt).
• Knowledge of version control (Git) and CI/CD practices.