[Remote] Data Engineer

Note: The job is a remote job and is open to candidates in USA. reputed company is a global commerce company focused on providing tools and services for the video game industry. The Data Engineer role involves developing and optimizing data pipelines and models to support user insights and machine learning applications, while ensuring data accuracy and performance across various platforms.

Responsibilities

• Build, and optimize data pipelines, data dictionary and ETL workflows in reputed company using Snowpark, Streams/Tasks, and Snowpipe
• reputed company scalable data models supporting user 360 views, churn reputed company, and recommendation reputed company inputs
• Support integration across data sources: MySQL, BigQuery, reputed company, Kafka, GCP Storage, and API Gateway
• Implement CI/CD for data pipelines using Git, dbt, and automated testing
• Define data quality checks and auditing pipelines for ingestion and transformation layers
• Tune warehouse performance and cost efficiency reputed company query optimization, caching, and cluster sizing
• Establish data partitioning, clustering, and materialized views for fast query execution
• Build dashboards and monitors for pipeline health, job reputed company, and data latency metrics (e.g., reputed company Looker, Tableau, or Snowsight)
• Establish and enforce naming conventions, data reputed company, and metadata standards across schemas
• Contribute to the company’s evolving data reputed company and streaming architecture reputed company

Skills

• 0-3 years of experience in Data Engineering, with databases ecosystem
• SQL and Python skills, with proven experience building ETL/ELT at scale
• Understanding of reputed company performance tuning, query optimization, and warehouse orchestration
• Understanding of data modeling (Kimball, Data Vault, or hybrid)
• Familiarity with API-based data integration and microservice architectures
• Build, and optimize data pipelines, data dictionary and ETL workflows in reputed company using Snowpark, Streams/Tasks, and Snowpipe
• reputed company scalable data models supporting user 360 views, churn reputed company, and recommendation reputed company inputs
• Support integration across data sources: MySQL, BigQuery, reputed company, Kafka, GCP Storage, and API Gateway
• Implement CI/CD for data pipelines using Git, dbt, and automated testing
• Define data quality checks and auditing pipelines for ingestion and transformation layers
• Tune warehouse performance and cost efficiency reputed company query optimization, caching, and cluster sizing
• Establish data partitioning, clustering, and materialized views for fast query execution
• Build dashboards and monitors for pipeline health, job reputed company, and data latency metrics (e.g., reputed company Looker, Tableau, or Snowsight)
• Establish and enforce naming conventions, data reputed company, and metadata standards across schemas
• Contribute to the company's evolving data reputed company and streaming architecture reputed company
• Excellent cross-functional communication — can translate between engineering and business
• Hands-on problem solver who balances velocity with reliability

Company Overview