GCP Data Engineer - Data Warehouse Migration (Contract)

SYMHAS L.L.C.
Denver, United States of America
5 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 135K

Job location

Denver, United States of America

Tech stack

API
Airflow
Google BigQuery
Cloud Computing Security
Cloud Storage
Continuous Integration
Data Validation
Information Engineering
ETL
Data Warehousing
Dimensional Modeling
Data Flow Control
Github
Identity and Access Management
Python
Microsoft SQL Server
Oracle Applications
Cloudera
SQL Stored Procedures
SQL Databases
Teradata
Google Cloud Platform
Cloud Platform System
Netezza
Snowflake
Build Server
GIT
Database Migration
PySpark
Infrastructure Automation Frameworks
Data Lineage
Terraform
Code Restructuring
Looker Analytics
Data Pipelines

Job description

We are seeking a GCP Data Engineer to drive a large-scale data warehouse migration to Google Cloud Platform. The role involves migrating legacy on-prem data warehouse workloads to BigQuery, re-engineering ETL/ELT pipelines, validating data quality and reconciliation, and optimizing performance and cost in the target environment. You will work closely with data architects, analysts, and business stakeholders to deliver a reliable, well-governed cloud data platform., * Cloud Platform: Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Composer)

  • Migration Tooling: BigQuery Migration Service, Database Migration Service, Datastream
  • Languages: SQL, Python, PySpark
  • Orchestration: Cloud Composer (Airflow), dbt
  • Source Systems: Legacy EDWs (Teradata / Oracle / SQL Server / Netezza), flat files, APIs
  • Data Modeling: Dimensional modeling (star/snowflake), partitioning and clustering strategies in BigQuery
  • DevOps: Git, CI/CD (Cloud Build / GitHub Actions), Terraform
  • Governance & Quality: Dataplex, data lineage, reconciliation and validation frameworks, IAM and security best practices, * Migrate legacy data warehouse schemas, historical data, and workloads to BigQuery, including SQL translation and refactoring of stored procedures and ETL logic
  • Design, build, and optimize batch and streaming pipelines using Dataflow, Dataproc/PySpark, Pub/Sub, and Cloud Composer
  • Perform data validation and reconciliation between source and target systems to ensure completeness, accuracy, and auditability
  • Optimize BigQuery performance and cost through partitioning, clustering, materialized views, and workload tuning
  • Implement CI/CD and infrastructure-as-code practices for data pipelines and GCP resources
  • Collaborate with architects, analysts, and business teams on cutover planning, parallel-run testing, and post-migration support

Requirements

Work Authorization: Only U.S. Citizens and Green Card holders will be considered. Candidates must be able to work on our W2., * 6+ years of data engineering experience, including 3+ years hands-on with GCP data services (BigQuery, Dataflow, Cloud Composer)

  • Proven experience with at least one end-to-end data warehouse migration to BigQuery (e.g., from Teradata, Oracle, SQL Server, or Netezza)
  • Expert-level SQL and strong Python/PySpark skills, including translating and optimizing complex legacy SQL for BigQuery
  • Solid understanding of dimensional data modeling, data quality/reconciliation frameworks, and cloud security/IAM fundamentals
  • Nice to have: GCP Professional Data Engineer certification, dbt, Datastream/CDC pipelines, and Looker or other BI tools

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