Overview
Skills
Job Details
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).
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Technical Skills: Strong SQL and Python skills with experience in query optimization and performance tuning.
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Education: Bachelor's degree in Computer Science, Information Technology, or a related field.
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Soft Skills: Strong analytical, problem-solving, and communication skills.
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Data Engineering Skills: Experience in building, maintaining, and optimizing data pipelines and ETL processes.
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Data Modeling: Knowledge of data warehousing concepts and hands-on experience in data modeling, particularly within Snowflake.
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Additional Tools and Platforms: Experience with additional ETL tools, data transformation methods, or cloud platforms is a plus.
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Healthcare and PBM: PBM-specific knowledge and experience with transforming various healthcare data is a plus, but not required.
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Design, develop, and maintain scalable and high-performance ETL pipelines using Matillion ETL to ingest, transform, and load data into Snowflake.
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Integrate and manage data from various sources, ensuring data quality, reliability, and performance.
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Optimize SQL queries, scripts, and stored procedures in Snowflake and SQL Server to improve efficiency and reduce processing time.
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Develop and implement data models within Snowflake to support business intelligence and analytics requirements.
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Collaborate with data architects and analysts to design and enhance data warehouse schemas and ensure alignment with reporting and analytics needs.
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Work with business stakeholders to understand data requirements and translate them into technical specifications.
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Support data architects and analysts by guiding data ingestion, storage, and retrieval methods.
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Monitor data pipeline and ETL performance, identifying bottlenecks and making necessary adjustments to ensure optimal system performance.
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Perform troubleshooting and root cause analysis to resolve data issues and prevent future occurrences.