Description

You will manage complex data pipelines and architecture to transform raw data into actionable business insights.

Responsibilities

• Develop and maintain data models, mapping rules, and data dictionaries to ensure data usability.
• Design and implement tiered data architectures that integrate analytics data from multiple sources.
• Build data validation and reconciliation processes to maintain high data quality and accuracy.
• Collaborate with analytics and business teams to define data governance policies and standards.
• Engineer ETL processes and data warehousing solutions to support reporting requirements.

Required Skills

• 7+ years of experience in Information Technology.
• 3+ years of hands-on experience with Hadoop distributed frameworks and the Hadoop ecosystem.
• 2+ years of experience using Spark or PySpark for large-scale data processing.
• 2+ years of professional experience with Scala or Python.
• Proficiency in SQL and major data analytics platforms.
• Strong understanding of data modeling, data warehousing, and ETL concepts.
• Proven experience in data engineering or data architecture.

Preferred Skills

• Knowledge of Design Patterns and ability to evaluate RDBMS vs Distributed Storage tradeoffs.
• Experience with data orchestration tools such as Airflow.

Key Skills

Education

Any Graduate