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

OSI Digital, Inc.; Dallas (TX); Hybrid; USD 100,000 - 150,000; Full time

Job summary

OSI Digital, Inc. is seeking a Data Engineer / BI Developer for a hybrid Dallas role. You will build cloud data pipelines and analytical reporting using GCP, Airflow, dbt, SQL, and Power BI.

The ideal candidate has 2–4 years of relevant experience and will design scalable data models, dashboards, and ETL/ELT processes. Collaborate with stakeholders and ensure data quality across pipelines.

Qualifications

• 2–4 years of data engineering, BI, or analytics experience.
• Hands-on with Google BigQuery and Power BI.
• Experience with Apache Airflow and dbt.
• Strong SQL and data modeling knowledge.
• Git or version-control experience.

Responsibilities

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

Skills

BigQuery

Airflow

dbt Core/Cloud

Power BI

SQL

Data Modeling

Git

Python

Tools

GCP

BigQuery UI

Databricks

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