Description

You will design and implement scalable data architecture solutions using AWS and Databricks.

This role is on-site.

Responsibilities

• Develop and maintain ETL pipelines and workflows using Apache Airflow.
• Process and analyze large datasets using Spark, PySpark, and SparkSQL.
• Conduct data modeling and warehousing to support analytics and BI initiatives.
• Automate data processing tasks using Python scripts and frameworks.
• Collaborate with cross-functional teams to gather requirements and deliver high-quality data solutions.

Required Skills

• 8+ years of experience in data architecture or engineering.
• Strong expertise in Apache Spark, PySpark, SparkSQL, and Python for big data processing.
• Hands-on experience with AWS services including S3, Redshift, EMR, and Glue.
• Knowledge of ETL pipelines, Airflow, and data orchestration tools.
• Proficiency in data modeling, data warehousing, and advanced SQL.
• Experience with version control (Git) for managing data projects.
• Familiarity with Databricks for data engineering and machine learning workloads.

Preferred Skills

• Any Graduate degree.

Key Skills

Education

Any Graduate