Position Overview:
We are looking for an experienced Data Engineer with a strong foundation in data engineering best practices and experience with modern data warehousing and ETL platforms. The ideal candidate will have at least 5 years of hands-on experience, preferably with Snowflake, SQL Server, AWS, and Matillion ETL, to build, optimize, and maintain data pipelines and data integration solutions. This role involves working closely with cross-functional teams to support data-driven initiatives across the organization.
SKILLS:Matillion, Snowflake, SQL, AWS Cloud
Required Qualifications:Experience: At least 5 years of experience in data engineering, with proficiency in Snowflake, SQL Server, AWS and ETL tools (preferably Matillion).
Technical Skills: Strong SQL and Python skills with experience in query optimization and performance tuning.
Education: Bachelor's degree in Computer Science, Information Technology, or a related field.
Soft Skills: Strong analytical, problem-solving, and communication skills.
Data Engineering Skills: Experience in building, maintaining, and optimizing data pipelines and ETL processes.
Data Modeling: Knowledge of data warehousing concepts and hands-on experience in data modeling, particularly within Snowflake.
Additional Tools and Platforms: Experience with additional ETL tools, data transformation methods, or cloud platforms is a plus.
Healthcare and PBM: PBM-specific knowledge and experience with transforming various healthcare data is a plus, but not required.
Design, develop, and maintain scalable and high-performance ETL pipelines using Matillion ETL to ingest, transform, and load data into Snowflake.
Integrate and manage data from various sources, ensuring data quality, reliability, and performance.
Optimize SQL queries, scripts, and stored procedures in Snowflake and SQL Server to improve efficiency and reduce processing time.
Develop and implement data models within Snowflake to support business intelligence and analytics requirements.
Collaborate with data architects and analysts to design and enhance data warehouse schemas and ensure alignment with reporting and analytics needs.
Work with business stakeholders to understand data requirements and translate them into technical specifications.
Support data architects and analysts by guiding data ingestion, storage, and retrieval methods.
Monitor data pipeline and ETL performance, identifying bottlenecks and making necessary adjustments to ensure optimal system performance.
Perform troubleshooting and root cause analysis to resolve data issues and prevent future occurrences.