Data Engineer

Overview

We are looking for a Senior Data Engineer to design, build, and maintain scalable data pipelines and data platforms that support analytics, reporting, and machine learning initiatives. The ideal candidate should have strong expertise in data architecture, ETL/ELT processes, and modern cloud-based data platforms, along with the ability to work closely with data scientists, analysts, and engineering teams.

Key Responsibilities

• Design, develop, and maintain scalable and reliable data pipelines for ingesting, processing, and transforming large volumes of data.
• Build and optimize ETL/ELT workflows for structured and unstructured data sources.
• Develop and manage data warehouses, data lakes, and data marts.
• Ensure data quality, integrity, and security across all data systems.
• Work closely with data scientists, analysts, and product teams to support data-driven initiatives.
• Optimize database performance and troubleshoot data pipeline failures or performance issues.
• Implement data governance, monitoring, and documentation best practices.
• Mentor junior data engineers and contribute to improving data engineering standards.
• Collaborate with DevOps teams for CI/CD pipelines and deployment of data solutions.
  
  

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
• 6+ years of experience in Data Engineering or related roles.
• Strong experience with Python, SQL, and data processing frameworks.
• Hands-on experience with ETL tools and data pipeline orchestration tools (Airflow, Prefect, etc.).
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Expertise in data warehousing solutions such as Snowflake, Redshift, BigQuery, or Azure Synapse.
• Experience working with big data technologies such as Spark, Hadoop, or Kafka.
• Strong understanding of data modeling and database design.
• Familiarity with version control systems and CI/CD practices.