Lead Data Engineer
Altis Technology
Data Engineering Lead
Location:
Toronto, ON - hybrid 3x week downtown TorontoIndustry:
Healthcare / Research
About the Opportunity
Altis Recruitment is partnering with a leading healthcare and research organization in Toronto to recruit an experienced
Data Engineering Lead .
This is an exciting opportunity for a hands-on technical leader to support and enhance established research data warehouse environments, drive data integration initiatives, and contribute to the development of scalable, secure, and reliable data platforms.
The successful candidate will bring strong expertise in
SQL, Python, and Apache NiFi, combined with a solid background in data architecture, data modelling, and cloud technologies.
This role is ideal for someone who enjoys remaining hands-on with development while providing technical guidance, establishing engineering best practices, and collaborating with cross-functional teams. The focus is on
technical leadership rather than traditional people management .
Your Responsibilities
Lead the design, development, optimization, and maintenance of data engineering solutions supporting research data warehouses and enterprise data platforms.
Design, build, and maintain robust ETL/ELT pipelines using
SQL, Python, and Apache NiFi .
Provide hands-on technical leadership, guidance, and mentorship to data engineering team members.
Support and enhance multiple established data systems while identifying opportunities for modernization, integration, and performance improvements.
Develop and maintain data architectures, data models, database schemas, and integration frameworks.
Collaborate with technical teams to establish data engineering standards, architecture patterns, and development best practices.
Support cloud-based and hybrid data environments, including Azure and/or Google Cloud Platform (GCP).
Implement data quality controls, validation processes, monitoring, metadata management, and data lineage practices.
Troubleshoot complex data integration, pipeline performance, and data quality issues.
Collaborate with research, analytics, infrastructure, security, and other stakeholders to deliver reliable data solutions.
Support data governance, privacy, access controls, and secure handling of sensitive information.
Evaluate emerging technologies and recommend improvements to existing data engineering processes and platforms.
Skills and Qualifications
7+ years of experience in data engineering, software engineering, data architecture, or a related technical discipline.
Strong hands-on experience with
SQL, Python, and Apache NiFi .
Proven experience designing, developing, and supporting ETL/ELT pipelines and complex data integration solutions.
Strong understanding of data warehousing concepts, data modelling, schema design, and database optimization.
Experience working with cloud technologies, particularly
Microsoft Azure and/or Google Cloud Platform (GCP) .
Demonstrated ability to provide technical leadership, conduct architecture reviews, and mentor engineers while remaining actively involved in development.
Experience supporting mature, complex data environments involving multiple systems and data sources.
Knowledge of data quality, orchestration, testing, monitoring, and CI/CD practices.
Experience collaborating with cross-functional technical teams and communicating architectural decisions effectively.
Strong problem-solving, analytical, and stakeholder communication skills.
What Makes This Opportunity Unique?
Technical Leadership:
Guide engineering practices and technical decisions while continuing to work hands-on with data engineering solutions.
Complex Data Environment:
Work with established research data platforms and contribute to their ongoing development and modernization.
Meaningful Impact:
Support data infrastructure and research initiatives that contribute to advancements in healthcare and mental health research.
Collaborative Environment:
Partner with engineers, researchers, architects, and technical stakeholders across multiple teams.
We appreciate the time and effort all applicants invest in their submissions. Please note that only candidates shortlisted for this role will be contacted directly. However, your profile will remain under consideration for future opportunities that align with your experience and career goals.
All qualified applicants will receive fair consideration for employment. We welcome individuals of all backgrounds, experiences, and identities including those who identify as women, members of racialized groups, Indigenous Peoples, persons with disabilities, and 2SLGBTQIA+ communities. If you require an accommodation, please review our accessibility policy and reach out to our accessibility officer with any questions.
Our human recruiters review all applications and always make the final hiring decision. On occasion, we also use AI-assisted tools to help review applications.
#J-18808-Ljbffr
Location:
Toronto, ON - hybrid 3x week downtown TorontoIndustry:
Healthcare / Research
About the Opportunity
Altis Recruitment is partnering with a leading healthcare and research organization in Toronto to recruit an experienced
Data Engineering Lead .
This is an exciting opportunity for a hands-on technical leader to support and enhance established research data warehouse environments, drive data integration initiatives, and contribute to the development of scalable, secure, and reliable data platforms.
The successful candidate will bring strong expertise in
SQL, Python, and Apache NiFi, combined with a solid background in data architecture, data modelling, and cloud technologies.
This role is ideal for someone who enjoys remaining hands-on with development while providing technical guidance, establishing engineering best practices, and collaborating with cross-functional teams. The focus is on
technical leadership rather than traditional people management .
Your Responsibilities
Lead the design, development, optimization, and maintenance of data engineering solutions supporting research data warehouses and enterprise data platforms.
Design, build, and maintain robust ETL/ELT pipelines using
SQL, Python, and Apache NiFi .
Provide hands-on technical leadership, guidance, and mentorship to data engineering team members.
Support and enhance multiple established data systems while identifying opportunities for modernization, integration, and performance improvements.
Develop and maintain data architectures, data models, database schemas, and integration frameworks.
Collaborate with technical teams to establish data engineering standards, architecture patterns, and development best practices.
Support cloud-based and hybrid data environments, including Azure and/or Google Cloud Platform (GCP).
Implement data quality controls, validation processes, monitoring, metadata management, and data lineage practices.
Troubleshoot complex data integration, pipeline performance, and data quality issues.
Collaborate with research, analytics, infrastructure, security, and other stakeholders to deliver reliable data solutions.
Support data governance, privacy, access controls, and secure handling of sensitive information.
Evaluate emerging technologies and recommend improvements to existing data engineering processes and platforms.
Skills and Qualifications
7+ years of experience in data engineering, software engineering, data architecture, or a related technical discipline.
Strong hands-on experience with
SQL, Python, and Apache NiFi .
Proven experience designing, developing, and supporting ETL/ELT pipelines and complex data integration solutions.
Strong understanding of data warehousing concepts, data modelling, schema design, and database optimization.
Experience working with cloud technologies, particularly
Microsoft Azure and/or Google Cloud Platform (GCP) .
Demonstrated ability to provide technical leadership, conduct architecture reviews, and mentor engineers while remaining actively involved in development.
Experience supporting mature, complex data environments involving multiple systems and data sources.
Knowledge of data quality, orchestration, testing, monitoring, and CI/CD practices.
Experience collaborating with cross-functional technical teams and communicating architectural decisions effectively.
Strong problem-solving, analytical, and stakeholder communication skills.
What Makes This Opportunity Unique?
Technical Leadership:
Guide engineering practices and technical decisions while continuing to work hands-on with data engineering solutions.
Complex Data Environment:
Work with established research data platforms and contribute to their ongoing development and modernization.
Meaningful Impact:
Support data infrastructure and research initiatives that contribute to advancements in healthcare and mental health research.
Collaborative Environment:
Partner with engineers, researchers, architects, and technical stakeholders across multiple teams.
We appreciate the time and effort all applicants invest in their submissions. Please note that only candidates shortlisted for this role will be contacted directly. However, your profile will remain under consideration for future opportunities that align with your experience and career goals.
All qualified applicants will receive fair consideration for employment. We welcome individuals of all backgrounds, experiences, and identities including those who identify as women, members of racialized groups, Indigenous Peoples, persons with disabilities, and 2SLGBTQIA+ communities. If you require an accommodation, please review our accessibility policy and reach out to our accessibility officer with any questions.
Our human recruiters review all applications and always make the final hiring decision. On occasion, we also use AI-assisted tools to help review applications.
#J-18808-Ljbffr
Vacancy posted 3 hours ago
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