Data Engineer / BI Developer – GCP, dbt & Power BI

Osi Digital Inc; Dallas (TX); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Osi Digital Inc. is seeking a Data Engineer / BI Developer in Dallas, TX (Hybrid) with 2-4 years of cloud-based data pipelines, transformation frameworks, and reporting experience. Expertise in Google BigQuery, Apache Airflow, dbt, SQL, and Power BI is required for building data warehousing, ETL/ELT processes, and dashboards.

The role emphasizes optimization, data modeling, quality checks, and collaboration with stakeholders to translate requirements into scalable solutions.

Qualifications

• 2-4 years of experience in Data Engineering, Business Intelligence, or Analytics Engineering.
• Strong hands-on experience with Google BigQuery.
• Hands-on experience developing and maintaining Apache Airflow DAGs.
• Good experience with dbt Core or dbt Cloud.
• Strong knowledge of SQL and query optimization.
• Hands-on experience with Power BI.
• Good understanding of Power Query, DAX, Data modeling, Power BI Service, Dataset / semantic model refresh, Row-Level Security (RLS).
• Understanding of ETL/ELT architecture and data warehousing concepts.
• Experience working with fact and dimension models and star-schema-based reporting solutions.
• Knowledge of data validation, reconciliation, and troubleshooting techniques.
• Experience using Git or similar version-control tools.
• Snowflake
• Databricks
• Python for data engineering
• GCP services: Cloud Storage, Cloud Composer, IAM, Dataflow, Pub/Sub
• Azure or AWS
• CI/CD pipelines for dbt, Airflow, or Power BI deployments
• Data governance, data quality, metadata management, and security concepts
• Agile/Scrum delivery environments

Responsibilities

• Design, develop, and maintain scalable data pipelines using Apache Airflow.
• Develop and optimize data warehouse solutions using Google BigQuery.
• Build reusable and maintainable transformation models using dbt.
• Develop interactive reports and dashboards using Power BI.
• Write complex and optimized SQL queries for extraction, transformation, validation, and reporting.
• Create and maintain dimensional models, fact tables, views, and reporting datasets.
• Develop dbt models, tests, documentation, macros, and incremental processing logic.
• Monitor Airflow DAGs and troubleshoot pipeline and data-quality issues.
• Optimize BigQuery queries for performance and cost efficiency.
• Build Power BI semantic models, relationships, measures, calculated columns, and DAX calculations.
• Perform source-to-target validation and data reconciliation.
• Implement data-quality checks to ensure reliable and consistent reporting.
• Participate in code reviews, deployments, testing, and production support.
• Maintain technical documentation for pipelines, transformations, datasets, and dashboards.

Skills

Data engineering

BI development

Analytics engineering

Cloud data platforms

Tools

Google BigQuery

Apache Airflow

dbt Core

dbt Cloud

SQL

Power BI

Git

Python

Power Query

DAX

Power BI Service

RLS

Job description

Job Title: Data Engineer / BI Developer - GCP, dbt & Power BI

Experience: 3-5 Years

Employment Type: Full-Time

Location: Dallas,TX Hybrid

Job Summary

We are looking for a Data Engineer / BI Developer with 2-4 years of experience in building cloud-based data pipelines, transformation frameworks, and analytical reporting solutions.

The ideal candidate should have hands‑on experience with Google BigQuery, Apache Airflow, dbt, SQL, and Power BI, along with a good understanding of data warehousing, ETL/ELT processes, data modeling, and dashboard development.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Apache Airflow.
• Develop and optimize data warehouse solutions using Google BigQuery.
• Build reusable and maintainable transformation models using dbt.
• Develop interactive reports and dashboards using Power BI.
• Write complex and optimized SQL queries for extraction, transformation, validation, and reporting.
• Create and maintain dimensional models, fact tables, views, and reporting datasets.
• Develop dbt models, tests, documentation, macros, and incremental processing logic.
• Monitor Airflow DAGs and troubleshoot pipeline and data‑quality issues.
• Optimize BigQuery queries for performance and cost efficiency.
• Build Power BI semantic models, relationships, measures, calculated columns, and DAX calculations.
• Perform source‑to‑target validation and data reconciliation.
• Implement data‑quality checks to ensure reliable and consistent reporting.
• Participate in code reviews, deployments, testing, and production support.
• Maintain technical documentation for pipelines, transformations, datasets, and dashboards.

Required Skills

• 2-4 years of experience in Data Engineering, Business Intelligence, or Analytics Engineering.
• Strong hands‑on experience with Google BigQuery.
• Hands‑on experience developing and maintaining Apache Airflow DAGs.
• Good experience with dbt Core or dbt Cloud.
• Strong knowledge of SQL and query optimization.
• Hands‑on experience with Power BI.
• Good understanding of:
  • Power Query
  • DAX
  • Data modeling
  • Power BI Service
  • Dataset / semantic model refresh
  • Row‑Level Security (RLS)
• Understanding of ETL/ELT architecture and data warehousing concepts.
• Experience working with fact and dimension models and star‑schema‑based reporting solutions.
• Knowledge of data validation, reconciliation, and troubleshooting techniques.
• Experience using Git or similar version‑control tools.

Added Advantage / Good to Have

• Any hands‑on experience with Snowflake will be an added advantage.
• Any experience with Databricks, Apache Spark, or Lakehouse architecture will be an added advantage.
• Experience with Python for data engineering or automation.
• Knowledge of additional GCP services such as:
  • Cloud Storage
  • Cloud Composer
  • IAM
  • Dataflow
  • Pub/Sub
• Exposure to other cloud platforms such as Azure or AWS.
• Experience with CI/CD pipelines for dbt, Airflow, or Power BI deployments.
• Understanding of data governance, data quality, metadata management, and security concepts.
• Experience working in Agile/Scrum delivery environments.

Preferred Candidate Profile

The candidate should be capable of independently developing data pipelines and reporting solutions, troubleshooting technical issues, and working with business and technical stakeholders to translate requirements into scalable data solutions. Candidates with broader modern data‑platform exposure, particularly Snowflake and Databricks, will be preferred.

Primary Technology Stack: GCP | BigQuery | Airflow | dbt | SQL | Power BI | Git | Python

Additional Advantage: Snowflake | Databricks | Spark | Azure | AWS