FlightSafety International
FlightSafety International is the world’s premier professional aviation training company and supplier of flight simulators, visual systems and displays to commercial, government and military organizations. The company provides training for pilots, technicians and other aviation professionals from 167 countries and independent territories. FlightSafety operates the world’s largest fleet of advanced full-flight simulators and award-winning maintenance training at Learning Centers and training locations in the United States, Canada, France and the United Kingdom.
Purpose of Position The Lead Data Engineer is a hands-on technical leader responsible for architecting, developing, and guiding the implementation of modern data solutions in a cloud-based environment. This role provides technical leadership to
Senior Data Engineers
and
Senior Analytics Engineers , ensuring best practices in data engineering, analytics, and reporting. The Lead Data Engineer plays a key role in strategic initiatives, driving the design and delivery of scalable data platforms, and enabling actionable insights through advanced Power BI dashboards and reports.
Tasks and Responsibilities
Serve as the
technical lead
on data engineering and analytics initiatives, ensuring alignment with architectural standards and business goals
Provide
technical mentorship and guidance
to Senior Data Engineers and Senior Analytics Engineers
Design and implement scalable ETL/ELT pipelines using
Azure Data Factory (ADF) ,
Databricks , and
DBT
Lead the development of
Data Vault 2.0
models and ensure consistency across projects
Architect and orchestrate data workflows using
Databricks LakeFlow ,
Apache Airflow , and ADF
Oversee data ingestion and replication strategies using tools such as Fivetran, SQDR, Rivery, or custom Python scripts
Develop and optimize
Power BI
dashboards, reports, and semantic models to support business intelligence and self-service analytics
Collaborate with business stakeholders, architects, and analysts to translate requirements into technical solutions
Ensure data quality, governance, and security standards are met across all data products
Lead code reviews, enforce development standards, and promote best practices in data engineering and analytics
Support CI/CD automation, DevOps practices, and version control for data pipelines and reporting assets
Troubleshoot and resolve complex data issues in production and development environments
Contribute to enterprise data strategy and participate in architectural review boards
Maintain documentation for data architecture, pipelines, and reporting solutions
Infrequent travel as needed
Bachelor's degree from an accredited institution or equivalent industry experience
12+ years of experience in data engineering or software development roles
3+ years in a technical leadership or lead engineer capacity
5+ years of experience with
Azure Data Factory
and
Azure Data Lake Storage
3+ years of experience with
Databricks ,
Delta Live Tables , and
Unity Catalog
3+ years of experience with
Power BI
dashboard and report development
2+ years of experience with
DBT
and
Apache Airflow
Experience with
Data Vault 2.0
modeling (certification preferred)
Strong experience with Python, PySpark, and SQL
Knowledge, Skills, Abilities
Deep expertise in
cloud data platforms , especially
Azure
and
Databricks
Strong understanding of
ELT/ETL , data modeling, and data warehousing principles
Proven ability to lead and mentor technical teams in a collaborative environment
Advanced skills in
Power BI , including DAX, Power Query, and data modeling
Experience with data ingestion and replication tools (e.g., Fivetran, SQDR, Rivery)
Proficiency in Python, PySpark, and SQL for data transformation and automation
Experience orchestrating workflows using
Apache Airflow
and
Databricks LakeFlow
Familiarity with DevOps, CI/CD pipelines, and version control systems (Git, TFS)
Strong communication and stakeholder engagement skills
Knowledge of data governance, metadata management, and compliance frameworks
Experience with Agile/Scrum methodologies
Exposure to AI/ML tools and concepts within
Databricks
is a plus
Experience in Education or Aviation industries is a plus
#J-18808-Ljbffr
Purpose of Position The Lead Data Engineer is a hands-on technical leader responsible for architecting, developing, and guiding the implementation of modern data solutions in a cloud-based environment. This role provides technical leadership to
Senior Data Engineers
and
Senior Analytics Engineers , ensuring best practices in data engineering, analytics, and reporting. The Lead Data Engineer plays a key role in strategic initiatives, driving the design and delivery of scalable data platforms, and enabling actionable insights through advanced Power BI dashboards and reports.
Tasks and Responsibilities
Serve as the
technical lead
on data engineering and analytics initiatives, ensuring alignment with architectural standards and business goals
Provide
technical mentorship and guidance
to Senior Data Engineers and Senior Analytics Engineers
Design and implement scalable ETL/ELT pipelines using
Azure Data Factory (ADF) ,
Databricks , and
DBT
Lead the development of
Data Vault 2.0
models and ensure consistency across projects
Architect and orchestrate data workflows using
Databricks LakeFlow ,
Apache Airflow , and ADF
Oversee data ingestion and replication strategies using tools such as Fivetran, SQDR, Rivery, or custom Python scripts
Develop and optimize
Power BI
dashboards, reports, and semantic models to support business intelligence and self-service analytics
Collaborate with business stakeholders, architects, and analysts to translate requirements into technical solutions
Ensure data quality, governance, and security standards are met across all data products
Lead code reviews, enforce development standards, and promote best practices in data engineering and analytics
Support CI/CD automation, DevOps practices, and version control for data pipelines and reporting assets
Troubleshoot and resolve complex data issues in production and development environments
Contribute to enterprise data strategy and participate in architectural review boards
Maintain documentation for data architecture, pipelines, and reporting solutions
Infrequent travel as needed
Bachelor's degree from an accredited institution or equivalent industry experience
12+ years of experience in data engineering or software development roles
3+ years in a technical leadership or lead engineer capacity
5+ years of experience with
Azure Data Factory
and
Azure Data Lake Storage
3+ years of experience with
Databricks ,
Delta Live Tables , and
Unity Catalog
3+ years of experience with
Power BI
dashboard and report development
2+ years of experience with
DBT
and
Apache Airflow
Experience with
Data Vault 2.0
modeling (certification preferred)
Strong experience with Python, PySpark, and SQL
Knowledge, Skills, Abilities
Deep expertise in
cloud data platforms , especially
Azure
and
Databricks
Strong understanding of
ELT/ETL , data modeling, and data warehousing principles
Proven ability to lead and mentor technical teams in a collaborative environment
Advanced skills in
Power BI , including DAX, Power Query, and data modeling
Experience with data ingestion and replication tools (e.g., Fivetran, SQDR, Rivery)
Proficiency in Python, PySpark, and SQL for data transformation and automation
Experience orchestrating workflows using
Apache Airflow
and
Databricks LakeFlow
Familiarity with DevOps, CI/CD pipelines, and version control systems (Git, TFS)
Strong communication and stakeholder engagement skills
Knowledge of data governance, metadata management, and compliance frameworks
Experience with Agile/Scrum methodologies
Exposure to AI/ML tools and concepts within
Databricks
is a plus
Experience in Education or Aviation industries is a plus
#J-18808-Ljbffr