GCP Data Engineer - Data Warehouse Migration (Contract)

SYMHAS L.L.C.

Denver, CO, United States

23 days ago

Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

3 years minimum

Compensation

$128,960.0 - $135,200.0

Working hours

Regular working hours

Job source

www.indeed.com

Tech stack

Application Programming Interfaces (APIs) Airflow BigQuery Cloud Computing Security Cloud Storage Continuous Integration Data Validation Information Engineering Extract Transform Load (ETL) Data Warehousing Dimensional Modeling Data Flow Control

+23 more

Github Identity and Access Management Python (Programming Language) Microsoft SQL Server Oracle (Applications) Cloudera SQL Stored Procedures SQL Databases Teradata SQL Google Cloud 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