Description

You will build, scale, and deploy data pipelines and architecture to support analytics, marketing, and data science teams.

Responsibilities

• Manage all aspects of data extraction, transfer, and load (ETL) activities.
• Develop data pipelines to make data available across multiple platforms.
• Execute data ingestion, cleaning, and curation into data warehouses and platforms.
• Design data and ML pipelines within the AI/ML ecosystem.
• Collaborate with DevOps and Architects to build scalable architectures for real-time and batch services.

Required Skills

• 5+ years of experience in data engineering or data science roles.
• Strong Python and SQL coding skills.
• 2+ years of experience building and performing ETL on AWS Redshift.
• Experience with distributed systems such as Spark.
• Proficiency with AWS data and ML technologies including Glue, MWAA, Data Pipeline, EMR, Athena, Redshift, and Lambda.
• Hands-on experience with orchestration tools like Airflow.
• Knowledge of data extraction techniques including CDC or time/batch-based methods using Debezium, AWS DMS, or Kafka Connect.
• Solid understanding of Data Warehousing, Data Modelling, and Data Analysis.
• Ability to troubleshoot performance issues regarding data ingestion, processing, and query execution on Redshift.

Preferred Skills

• Experience working with Kafka.

Key Skills

Education

Any Graduate