Description

You will engineer data solutions supporting reporting and analytic needs by building scalable data pipelines.

Responsibilities

• Engineer diverse data pipelines using technologies like Steramsets, dbt, and data ops.
• Design and model data for data warehousing and modern analytics use cases.
• Implement data orchestration processes for complex data flows.
• Analyze SQL and Python scripts to validate ETL/ELT transformations.

Required Skills

• 12+ years in data engineering, including data pipelines, data ops, scripting, and SQL.
• 5+ years in data architecture, accountable for data standards and data modeling.
• 3+ years experience in modern data architecture supporting advanced analytics (e.g., Azure, Snowflake).
• Expert in engineering ETL/ELT pipelines using big data technologies like Hive and Spark on large datasets.
• 5+ years hands-on experience in data warehouse design and modeling best practices.
• Highly proficient in Python or Java.
• Highly proficient in data analysis using SQL and Python.
• Experience with data orchestration tools like Apache Airflow.
• Bachelor’s Degree in Computer Science, Information Systems, Engineering, Business Analytics, or Business Management.

Key Skills

Education

Any Graduate