FlightSafety International
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
Minimum Education
Bachelor's degree from an accredited institution or equivalent industry experience
Minimum 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
Physical Demands and Work Environment The physical demands and work environment described here are representative of those that must be met and/or encountered by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to use hands to finger, handle, or feel; reach with hands and arms; and communicate. The employee may be required to stand, walk, and sit. Specific vision abilities required by this job include the ability to view monitors, technical documents, and reference material. The employee must occasionally lift or move up to 25 pounds. The noise level in the work environment is usually low to moderate.
FlightSafety is an Equal Opportunity Employer/Vet/Disabled. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability.
Cybersecurity Notice:
All official recruiting communication from FlightSafety International will come from an
@flightsafety.com
email address. FlightSafety International will never ask for personal or financial information through social media or third-party email providers.
#J-18808-Ljbffr
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
Minimum Education
Bachelor's degree from an accredited institution or equivalent industry experience
Minimum 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
Physical Demands and Work Environment The physical demands and work environment described here are representative of those that must be met and/or encountered by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to use hands to finger, handle, or feel; reach with hands and arms; and communicate. The employee may be required to stand, walk, and sit. Specific vision abilities required by this job include the ability to view monitors, technical documents, and reference material. The employee must occasionally lift or move up to 25 pounds. The noise level in the work environment is usually low to moderate.
FlightSafety is an Equal Opportunity Employer/Vet/Disabled. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability.
Cybersecurity Notice:
All official recruiting communication from FlightSafety International will come from an
@flightsafety.com
email address. FlightSafety International will never ask for personal or financial information through social media or third-party email providers.
#J-18808-Ljbffr