Senior Data Engineer

Pattern

$100K — $150K *
US-AnywhereRemote in San Mateo, CA
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Minimum 4 years in data engineering, analytics engineering, or software engineering focused on large-scale data systems.
  • Proficient in Python and advanced SQL for data manipulation and analysis.
  • Experienced with ETL pipelines and data warehouse management (Snowflake, BigQuery, Redshift).
  • Familiar with SQL RDBMS (MySQL, Postgres) and NoSQL databases (MongoDB).
  • Knowledgeable in using Meltano, dbt, Airflow, and Superset tools for data operations.
  • Adept with Docker, Git, and AWS services (EC2, ECS, S3, etc.).
  • Analytics and Business Intelligence expertise is preferred.

Responsibilities

  • Build and deploy data pipelines for the machine learning platform.
  • Develop warehouse architectures integrating data from various sources.
  • Design analytics solutions for product development and internal teams.

Benefits

  • Opportunity to work in a collaborative, data-focused environment.
  • Exposure to the latest tools and technologies in data engineering and analytics.
  • Professional development and training opportunities within the company.
  • Contribution to impactful projects that enhance machine learning capabilities.
Full Job Description
Job Description

We are looking for a savvy Data Engineer to join our growing team of data experts. The hire will be responsible for expanding and optimizing our data pipeline architecture, as well as optimizing data flow and collection for cross functional teams.

Responsibilities:
  • Build and deploy the data pipelines that power PatternAI's machine learning platform.
  • Develop warehouse architectures that integrate data from diverse sources.
  • Design analytics solutions for both product development and internal collaborators.


Qualifications

Experience:
  • A minimum of 4 years experience in data engineering, analytics engineering, or software engineering with an emphasis on large scale data management and processing systems.
  • Proficiency in Python and advanced SQL.
  • Advanced experience with ETL pipelines, data modeling and managing data warehouses (Snowflake, BigQuery, Redshift, etc).
  • Experience with SQL RDBMS such as MySQL, Postgres, Oracle, SQL Server, etc., as well as NoSQL systems such as MongoDB is required.
  • Experience with tools including Meltano, dbt, Airflow, and Superset is required.
  • Experience with Docker, Git and AWS (EC2, ECS, S3, Step Functions, and Athena).
  • Analytics and Business Intelligence knowledge is highly preferred.
  • Experience working with common SaaS APIs (such as CRMs) is preferred.


Additional Information

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