Data Engineer (Python / Snowflake / Kafka)

Data Engineer (Python / Snowflake / Kafka) Key Responsibilities

Design and build scalable data pipelines and data-processing solutions from the ground up.

Develop and maintain both batch ETL and real-time streaming pipelines .

Build data-processing solutions using Python and PySpark .

Work extensively with Snowflake and Kafka .

Participate in data architecture, design and technology decisions.

Develop solutions that can scale as additional data sources and use cases are introduced.

Partner with technical leads and cross-functional teams to define requirements and recommend solutions.

Establish engineering standards, processes and best practices for a growing data environment.

Support downstream data consumption, reporting and visualization needs.

Troubleshoot data pipeline, performance and integration issues.

Core Qualifications

Senior-level Data Engineering experience with strong hands-on development skills.

Strong Python and PySpark development experience.

Strong Snowflake experience.

Strong Kafka / real-time streaming experience.

Experience designing and developing ETL/data pipelines .

Experience with both batch and streaming data processing .

Strong SQL and data modeling fundamentals.

Experience helping design or build a data platform or major data environment from the ground up .

Ability to independently evaluate requirements, recommend solutions and drive technical work with minimal oversight.

Experience designing data solutions with scalability, reliability and performance in mind.

Additional / Preferred Experience

Experience with any of the following is beneficial:

DynamoDB

Oracle

Grafana

Cloud-based data platforms

High-volume consumer or digital data environments

Data visualization and downstream analytics solutions

Technical leadership or lead-level engineering responsibilities