Data Engineer

We are looking for a Data Engineer to join our dynamic team.

Key Responsibilities

  • Set up and manage Kafka clusters and Kafka Connect to handle real-time data flows.
  • Monitor and support streaming data pipelines, ensuring reliability, scalability, and performance.
  • Build and maintain data models in Snowflake to support reporting and analytics needs.
  • Optimize Snowflake usage for scalability and performance across teams.
  • Design and develop ETL workflows using AWS Glue to process both structured and unstructured data.
  • Utilize the AWS Glue Data Catalog to organize metadata and support querying through Amazon Athena.
  • Implement best practices for organizing and securing data stored in AWS S3.
  • Create and manage data workflows in Apache Airflow, ensuring timely and reliable ETL execution.
  • Troubleshoot failures and continuously improve orchestration processes.
  • Support data quality, governance, and access control initiatives to maintain trust in data assets.
  • Collaborate with data analysts, data scientists, and business stakeholders to deliver reliable and usable data.
  • Stay up to date with evolving tools and best practices in cloud data engineering.

Candidate Profile

  • Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
  • 2–3 years of hands-on experience in data engineering, with a focus on cloud platforms.
  • Practical experience with:
  • Kafka for real-time data processing.
  • Snowflake for data warehousing.
  • AWS Glue, Athena, and S3 for data processing and storage.
  • Apache Airflow for workflow orchestration.
  • Proficiency in SQL, Python, and shell scripting.
  • Solid understanding of data modeling and cloud security principles.

Preferred Qualifications

  • Exposure to Microsoft Azure or Google Cloud Platform (GCP).
  • Experience with CI/CD tools such as Jenkins or Git.
  • Familiarity with Docker or basic containerization concepts.

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