How Remoteville checks and expires listings

Senior Data Engineer

Skills
Data AnalyticsData ModelingData ModelsData QualityData WarehousingDatabasesExtract
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • 5+ years of experience building and maintaining data pipelines and automating data availability and accuracy.
  • Experience with Snowflake or similar cloud platforms.
  • Expertise in complex data modeling, ETL design, and handling large databases in a business environment.
  • Proven ability in building data lake and data warehouse solutions.
  • Advanced skills in writing and optimizing complex SQL.
  • Demonstrated efficiency in tracking data lineage, ensuring data quality, and improving discoverability of data.
  • Knowledge of Engineering and Operational Excellence best practices.

Nice to have

  • Knowledge of dbt.
  • Experience leading a small team.
  • Experience building data governance programs.
  • Familiarity with Kafka.

Day to day

  • Ensuring data availability and quality from OLTP systems to analytics environments.
  • Managing and maintaining data pipelines and high-volume data storage solutions, optimizing compute and storage consumption.
  • Developing and improving the current BI architecture with a focus on data security, quality, timeliness, scalability, and extensibility.
  • Analyzing source systems, defining underlying data sources, and designing end-to-end data solutions and architecture.
  • Writing high-quality code, providing quality code reviews, and creating comprehensive tests and documentation.
  • Developing and implementing complex data models, ETL processes, and data warehouse solutions.
  • Providing data leadership within the team by informing decisions and offering insights on data usage across the organization.
  • Collaborating with machine learning engineers, analysts, and data PMs to ensure data initiatives align with business goals.
  • Collaborating with SecOps and Engineering to ensure data security compliance, and the integration of best practices in data management.