Data Engineering Manager – GCP Cloud

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

📋 Description

• Design and implement scalable enterprise data platforms on Google Cloud Platform (GCP)

• Create Data Lake and Lakehouse frameworks utilizing Google Cloud Storage and BigQuery

• Define the Bronze, Silver, and Gold/Atomic data layers

• Oversee the complete migration of enterprise data platforms from AWS to GCP

• Evaluate AWS architecture, data pipelines, workloads, dependencies, and operational processes

• Establish target-state GCP architecture, migration roadmaps, phases, dependencies, risks, and rollback strategies

• Facilitate architecture reviews and lead technical design discussions

• Design real-time data pipelines utilizing Pub/Sub, Dataflow/Apache Beam, BigQuery, and Cloud Storage

• Create high-volume event ingestion, enrichment, and transformation pipelines

• Develop scalable batch and real-time ETL/ELT pipelines using Python, PySpark, SQL, Dataflow/Apache Beam, BigQuery, and dbt

• Construct orchestration workflows with Cloud Composer/Airflow

• Design enterprise data models for analytics and reporting purposes

• Optimize BigQuery partitioning, clustering, SQL, and query execution

• Establish standards for data governance, quality, lineage, metadata, ownership, and security

• Implement IAM, least-privilege access, encryption, service accounts, network security, and data access policies

• Lead infrastructure automation using Terraform and establish CI/CD pipelines

• Optimize performance and costs across BigQuery, Dataflow, Spark, Cloud Storage, and streaming workloads

• Mentor Data Engineers, Senior Data Engineers, and Technical Leads

• Provide technical guidance, conduct architecture and code reviews, and define roadmaps and engineering priorities

• Monitor engineering progress, risks, dependencies, and delivery milestones

• Serve as the main technical contact for stakeholders based in the US

• Collaborate with Business, Product, Data Science, BI, and DevOps teams

• Translate business requirements into scalable technical solutions while communicating risks, timelines, and trade-offs

⛳️ Requirements

• Over 15 years of experience in Data Engineering, Data Architecture, or Cloud Engineering

• More than 5 years of hands-on experience in GCP Data Engineering

• At least 3 years of demonstrated experience on AWS-to-GCP migration projects

• Extensive experience in designing enterprise Data Lake and Lakehouse platforms

• Experience in migrating AWS data workloads to GCP

• Strong understanding of AWS and GCP service mapping and cloud migration patterns

• Proficient in SQL and skilled in Python/PySpark

• Strong background in data modeling and data warehousing

• Familiarity with Terraform and CI/CD practices

• Experience in managing and mentoring data engineering teams

• Excellent communication skills, especially in collaboration with US-based stakeholders

• In-depth knowledge of Amazon S3, AWS Glue, AWS Glue Data Quality, Amazon Redshift/Redshift Serverless, Amazon Athena, AWS Step Functions, AWS DMS, AWS Lake Formation, and IAM

• Comprehensive experience with BigQuery, Google Cloud Storage, Pub/Sub, Dataflow/Apache Beam, Cloud Composer/Airflow, Dataproc/Spark, Cloud Monitoring, Cloud Logging, and Dataplex/Data Catalog

• Experience with ETL/ELT, Change Data Capture (CDC), batch and streaming data processing, event-driven architecture, and optimization of data pipelines

🏝️ Benefits

• Flexible remote work environment

• Opportunity to engage with global enterprise customers

• Collaborative and innovation-focused engineering culture

• Continuous learning and certification opportunities