Raks Group
Our client is seeking Senior Data Engineer to help modernize and scale our Business Intelligence data infrastructure. This role will be critical in transitioning our existing on-prem SQL Server–based dimensional data mart and SSIS pipelines into a cloud-native solution on Google Cloud Platform (GCP) using tools like DBT , BigQuery , and other GCP-native services.
This is a hands‑on engineering role focused on building robust, scalable data pipelines and enabling performant data models that power Tableau dashboards used throughout the organization.
Responsibilities
Lead the migration of the existing SSIS-based ETL workflows to cloud-native pipelines using DBT and / or GCP tools such as Dataflow, Dataform, or Cloud Composer (Airflow).
Design and implement scalable, efficient data models in BigQuery , following best practices for dimensional modeling.
Optimize and maintain existing SQL transformations, ensuring correctness and performance in the cloud.
Collaborate with BI developers and analysts to ensure data marts align with Tableau reporting needs.
Ensure data integrity, security, and lineage through testing, documentation, and observability practices.
Work with on‑prem teams to phase out legacy systems and design transitional architectures where needed.
Establish best practices and mentor junior engineers on cloud‑first data engineering patterns.
Qualifications: Required
5+ years of experience in data engineering with strong SQL and ETL skills.
Experience with SSIS and legacy SQL Server–based data marts.
Proficiency in Google BigQuery and / or similar cloud data warehouses.
Hands‑on experience with DBT or modern transformation frameworks.
Strong knowledge of dimensional modeling and data warehousing principles.
Experience migrating on‑prem pipelines to cloud platforms.
Familiarity with GCP‑native services such as Cloud Storage, Pub/Sub, Dataflow, Composer, and IAM.
Strong knowledge of Healthcare Information Systems.
Preferred
Experience supporting or integrating with Tableau‑based BI solutions.
Exposure to infrastructure‑as‑code tools like Terraform for GCP.
Knowledge of data observability tools and practices.
Comfortable with Git‑based CI/CD for data pipeline deployments.
Nice to Have
Familiarity with GCP networking and cost optimization strategies.
Experience with data validation or automated testing frameworks for pipelines.
Knowledge of metadata management or cataloging tools (e.g., Data Catalog, DataPlex).
What You’ll Bring
A builder’s mindset with a bias for simplification and automation.
A collaborative approach to working with BI and application teams.
The ability to balance long‑term platform scalability with short‑term deliverables.
A passion for cloud innovation and data platform modernization.
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This is a hands‑on engineering role focused on building robust, scalable data pipelines and enabling performant data models that power Tableau dashboards used throughout the organization.
Responsibilities
Lead the migration of the existing SSIS-based ETL workflows to cloud-native pipelines using DBT and / or GCP tools such as Dataflow, Dataform, or Cloud Composer (Airflow).
Design and implement scalable, efficient data models in BigQuery , following best practices for dimensional modeling.
Optimize and maintain existing SQL transformations, ensuring correctness and performance in the cloud.
Collaborate with BI developers and analysts to ensure data marts align with Tableau reporting needs.
Ensure data integrity, security, and lineage through testing, documentation, and observability practices.
Work with on‑prem teams to phase out legacy systems and design transitional architectures where needed.
Establish best practices and mentor junior engineers on cloud‑first data engineering patterns.
Qualifications: Required
5+ years of experience in data engineering with strong SQL and ETL skills.
Experience with SSIS and legacy SQL Server–based data marts.
Proficiency in Google BigQuery and / or similar cloud data warehouses.
Hands‑on experience with DBT or modern transformation frameworks.
Strong knowledge of dimensional modeling and data warehousing principles.
Experience migrating on‑prem pipelines to cloud platforms.
Familiarity with GCP‑native services such as Cloud Storage, Pub/Sub, Dataflow, Composer, and IAM.
Strong knowledge of Healthcare Information Systems.
Preferred
Experience supporting or integrating with Tableau‑based BI solutions.
Exposure to infrastructure‑as‑code tools like Terraform for GCP.
Knowledge of data observability tools and practices.
Comfortable with Git‑based CI/CD for data pipeline deployments.
Nice to Have
Familiarity with GCP networking and cost optimization strategies.
Experience with data validation or automated testing frameworks for pipelines.
Knowledge of metadata management or cataloging tools (e.g., Data Catalog, DataPlex).
What You’ll Bring
A builder’s mindset with a bias for simplification and automation.
A collaborative approach to working with BI and application teams.
The ability to balance long‑term platform scalability with short‑term deliverables.
A passion for cloud innovation and data platform modernization.
#J-18808-Ljbffr