Data Engineer – Google Cloud Platform BigQuery

Position: Sr. Data Engineer – Google Cloud Platform BigQuery (Data Warehouse Migration)

Location: 100% REMOTE

Duration: 6-12 Months [Extension or Conversion to FTE Possible]

Summary:

Looking for Data Migration / Data Warehouse Engineers with experience moving legacy data platforms such as Teradata, Hadoop, Databricks, Oracle, SQL Server, AWS, or Azure into Google Cloud Platform BigQuery.

BigQuery experience is needed with any of Databricks, Snowflake migration

Skills/Experience Needed:

• 6+ years in data engineering, ETL/ELT, analytics engineering, data warehouse development, or big data pipelines;
• 4 years on Google Cloud Platform cloud data platforms preferred.

Cloud & Data Warehouse

• Hands-on experience with BigQuery or another enterprise cloud data warehouse.
• Experience working with one or more legacy data platforms such as Teradata, Hadoop/Hive, Databricks, Oracle, SQL Server, Netezza, Redshift, Snowflake, or Azure Synapse.

Data Migration & Data Warehousing

• Experience in migration assessment, schema mapping, data profiling, and migration factory approaches.
• Strong understanding of dimensional modelling, fact and dimension table design, and SCD Type 1 & Type 2.
• Experience with schema evolution, historical data handling, data validation, reconciliation, parallel run, cutover, and rollback strategies.

Data Engineering

• Strong proficiency in SQL and Python.
• Experience designing, developing, and supporting ETL/ELT pipelines.
• Strong understanding of data modelling, data warehousing concepts, partitioning, clustering, indexing, and query optimization.
• Experience with cloud storage and data lake architectures.

Big Data & Pipeline Processing

• Hands-on experience with batch and streaming data pipelines.
• Experience with one or more of the following technologies: Spark / PySpark, Apache Beam, Google Cloud Dataflow, Dataproc, Databricks, Amazon EMR

Workflow Orchestration & DevOps

• Experience with orchestration tools such as Apache Airflow, Cloud Composer, Control-M, Azure Data Factory (ADF), dbt, or equivalent.
• Experience with CI/CD pipelines and Git-based code versioning.

Data Quality & Performance

• Experience implementing data quality checks, schema validation, data lineage, monitoring, and alerting.
• Ability to optimize data pipelines and warehouse performance.
• Ability to explain real-world architecture, scalability, and performance optimization scenarios—not just tool definitions.