Lead Snowflake Data Engineer

Job Summary:

• We are seeking an experienced Lead Snowflake Data Engineer to join our Data & Analytics team. This role involves designing, implementing, and optimizing Snowflake-based data solutions while providing strategic direction and leadership to a team of junior and mid-level data engineers. The ideal candidate will have deep expertise in Snowflake, cloud data platforms, ETL/ELT processes, and Medallion data architecture best practices. The lead data engineer role has a strong focus on performance optimization, security, scalability, and Snowflake credit control and management. This is a tactical role requiring independent in-depth data analysis and data discovery to understand our existing source systems, fact and dimension data models, and implement an enterprise data warehouse solution in Snowflake.

Essential Functions and Tasks:

• Lead the design, development, and maintenance of a scalable Snowflake data solution serving our enterprise data & analytics team.
• Architect and implement data pipelines, ETL/ELT workflows, and data warehouse solutions using Snowflake and related technologies.
• Optimize Snowflake database performance, storage, and security.
• Provide guidance on Snowflake best practices.
• Collaborate with cross-functional teams of data analysts, business analysts, data scientists, and software engineers, to define and implement data solutions.
• Ensure data quality, integrity, and governance across the organization.
• Provide technical leadership and mentorship to junior and mid-level data engineers.
• Troubleshoot and resolve data-related issues, ensuring high availability and performance of the data platform.

Education and Experience Requirements:

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
• 8+ years of experience in-depth data engineering, with at least 3+ minimum years of dedicated experience engineering solutions in a Snowflake environment.
• Tactical expertise in ANSI SQL, performance tuning, and data modeling techniques.
• Strong experience with cloud platforms (preference to Azure) and their data services.
• Proficiency in ETL/ELT development using tools such as Azure Data Factory, dbt, Matillion, Talend, or Fivetran.
• Hands-on experience with scripting languages like Python for data processing.
• Strong understanding of data governance, security, and compliance best practices.
• Snowflake SnowPro certification; preference to the engineering course path.
• Experience with CI/CD pipelines, DevOps practices, and Infrastructure as Code (IaC).
• Knowledge of streaming data processing frameworks such as Apache Kafka or Spark Streaming.
• Familiarity with BI and visualization tools such as PowerBI.

Knowledge, Skills, and Abilities:

• Familiarity working in an agile scum team, including sprint planning, daily stand-ups, backlog grooming, and retrospectives.
• Ability to self-manage large complex deliverables and document user stories and tasks through Azure Dev Ops.
• Personal accountability to committed sprint user stories and tasks.
• Strong analytical and problem-solving skills with the ability to handle complex data challenges.
• Ability to read, understand, and apply state/federal laws, regulations, and policies.
• Ability to communicate with diverse personalities in a tactful, mature, and professional manner.
• Ability to remain flexible and work within a collaborative and fast paced environment.
• Understand and comply with company policies and procedures.
• Strong oral, written, and interpersonal communication skills.
• Strong time management and organizational skills.

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