Snowflake Data Engineer

Job Title:- Snowflake Data Engineer

Location:- Raleigh,NC (Hybrid/2 Days onsite rest Remote)

Duration:- 6 Months Contract to hire

Required Responsibilities*
Design and implement scalable and efficient data pipelines to support various data-driven
initiatives.
Build reusable data solutions and ensure thorough documentation that facilitates
understanding and adoption across the team.
Rewrite and optimize SQL queries to improve execution times and reduce resource
consumption, ensuring efficient data retrieval and manipulation.
Create and maintain technical specification documents for Snowflake build
Document database designs, optimization strategies, and maintenance procedures to
facilitate knowledge sharing and adherence to best practices.
Demonstrate technical leadership by staying abreast of emerging data engineering
technologies and strategies, proactively recommending improvements to governance,
performance, and quality of data.
Collaborate with cross-functional teams to understand data requirements and contribute
to the development of data architectures.
Contribute to data modernization efforts by leveraging cloud solutions and optimizing
data processing workflows.
Ensure data integrity and security by implementing appropriate access controls and
compliance measures.

Qualifications**
BA/BS degree required (Computer Science preferred) with at least 7+ years' hands-on
experience in designing, configuring, implementing, and migrating data for enterprise
data platforms with at least 5+ years' working on data warehousing projects.
Strong understanding of data warehousing (specifically working with Kimball-style
dimensional models), data architecture, data quality processes, and database design,
both logical and physical.
Mastery of Advanced SQL, Python, Snowflake cloud data warehousing.
Extensive experience with cloud migration processes and tools, such as Snowflake,
Fivetran, dbt, Azure Data Factory, Azure Functions, and other Azure data services,
Proven ability to design and implement data ingestion processes for both structured and
unstructured data.
Comprehensive knowledge of data management, including master data, metadata
standards, and associated processes.
Expert within the Data & Analytics discipline, including dimensional modeling, ETL/ELT,
data warehousing, data collection, data transformation and quality checks on structured
and unstructured data. (Experience with DBT preferred.)
Knowledge of machine learning and data analytics concepts
Familiarity with data engineering frameworks and tools
A commitment to continuous learning and personal development.
Ability to translate business requirements and system specifications into technical
specifications and test plans
Ability to facilitate teams and lead decision-making processes in a collaborative
environment
Ability to communicate well and make effective presentations
Strong analytical and problem-solving skills
Understanding of the Agile mindset and Scrum practices