Data Engineer
3 weeks ago
Company Overview
This is for a fast-growing data and analytics consulting firm that partners with Fortune 500 companies across diverse industries to solve complex business challenges through data-driven insights. Their mission is to help organizations make smarter decisions by turning data into a strategic asset, enabling them to improve operations, boost performance, and enhance customer experiences. With a strong emphasis on innovation, agility, and technical expertise, Their teams work on cutting-edge technologies in AI, ML, and data engineering to provide end-to-end solutions tailored to clients' needs. They foster a collaborative, high-energy environment that encourages professional growth and values the unique contributions of each team member.
Job Overview
As a Snowflake Data Engineer, you will play a key role in designing and implementing robust, scalable data architectures and pipelines to support advanced analytics and data-driven decision-making. Youll work closely with cross-functional teams to understand business requirements and translate them into efficient, optimized data solutions. The ideal candidate will have a strong background in Snowflake and cloud data warehousing, with hands-on experience in data modeling, ETL processes, and performance tuning. This is an exciting opportunity for someone passionate about leveraging the power of Snowflake to drive business insights and transform raw data into valuable assets.
Qualifications and Skills
- Technical Expertise:
- Proficiency in Snowflake, including SnowSQL, Snowpipe, and Snowflake stored procedures.
- Strong SQL skills and experience in query optimization.
- Experience with data integration tools (e.g., Informatica, Talend, or similar).
- Familiarity with cloud platforms (Azure Data Factory) and cloud data solutions.
- Data Modeling: Proficient in data modeling techniques and database design.
- Scripting Languages: Experience with scripting languages such as Python or Java for data transformation and automation.
- ETL/ELT Knowledge: Strong knowledge of ETL/ELT concepts and best practices for data pipeline development.
- Data Security & Governance: Understanding of data privacy laws, security protocols, and data governance standards.
- Snowflake certification is a plus.
- Familiarity with big data frameworks such as PySpark or Hadoop.
- Knowledge of agile methodologies and DevOps practices.
- Strong problem-solving skills and ability to work in a fast-paced environment.
- Excellent communication and interpersonal skills.
- Strong analytical and problem-solving abilities.
- Ability to work both independently and as part of a collaborative team.
- Adaptability and eagerness to learn new technologies.
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