Description
Summary: We are seeking a highly skilled and detail-oriented Data Engineer with strong expertise in SQL and Python to join our growing data team. In this role, you will be responsible for building scalable and efficient data pipelines, transforming large volumes of data, and supporting data analytics initiatives across the organization.
Key Responsibilities:
Design, develop, and maintain robust data pipelines and ETL/ELT processes using Spark and SQL.
Process and transform large datasets from various sources to ensure high performance and data quality.
Optimize Spark jobs for performance, scalability, and cost-efficiency in distributed environments.
Work closely with data analysts, data scientists, and business stakeholders to understand data requirements and deliver solutions.
Build and manage data models and data marts in cloud data warehouses (e.g., Snowflake, Redshift, BigQuery).
Ensure data accuracy, integrity, and availability across systems.
Participate in code reviews, troubleshooting, and performance tuning of existing data processes.
Maintain documentation for data flows, transformations, and processes.
Required Skills & Qualifications:
~8+ years of experience as a Data Engineer or in a similar role.
~ Strong proficiency in SQL for data transformation, querying, and performance tuning.
~ Experience working with Python for large-scale data processing.
~ Familiarity with data lakes, data warehouses, and cloud data platforms (AWS, GCP, Azure).
~ Proficient in scripting languages such as Python.
~ Solid understanding of data modeling concepts and data architecture.
~ Experience with version control tools like Git.
~ Strong analytical and problem-solving skills.
~ Excellent communication and collaboration skills.
