Lead Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Architect and enhance large-scale data platforms on Google Cloud, utilizing BigQuery as the core analytical framework.

• Design and construct integrated batch and streaming pipelines capable of managing high-volume, mission-critical workloads.

• Lead practices in infrastructure-as-code, guaranteeing that environments are repeatable, secure, and version-controlled.

• Implement open table formats to facilitate cross-cloud and cross-engine data interoperability.

• Establish automated practices for data quality, metadata, and lineage across the entire data estate.

• Collaborate with data scientists, analysts, and product teams to convert business requirements into dependable data products.

• Mentor engineers, evaluate designs, and elevate engineering standards.

⛳️ Requirements

• Over 7 years of experience in data engineering, with a minimum of 2 years in a lead or senior individual contributor role on Google Cloud-based platforms.

• BigQuery (Advanced): Profound understanding of BigQuery architecture, including partitioning, clustering, slot management, storage optimization, and query execution tuning.

• Streaming & Batch Pipelines: Extensive hands-on experience in constructing unified pipelines using Dataflow (Apache Beam), Dataproc, and Pub/Sub.

• Infrastructure as Code: Practical experience in developing and managing cloud infrastructure with Terraform.

• Open Table Formats: Familiarity with Apache Iceberg, including its function in enabling interoperability across clouds and engines (e.g., BigQuery, Spark, Snowflake).

• Data Governance: Experience with Dataplex and Data Catalog for automated data quality assessments, metadata tagging, and column-level lineage from source to destination.

🏝️ Benefits

• Comprehensive Health Insurance

• Paid Leave (Vacation/PTO)

• Paid Holidays

• Sick Leave

• Parental Leave

• Bereavement Leave

• 401 (k) Employer Match

• Employee Referral Bonuses