Opens LinkedIn
- Employment type
- Contract
- Experience level
- Senior · 5+ years
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Not Applicable
- Application method
- Direct apply is available
Job summary
Lead the design, development, testing, and optimization of large-scale data pipelines and architectures aligned with business and solution architecture requirements. Provide technical leadership, collaborate with business teams, and oversee high-quality data solutions that support predictive and prescriptive analytics.
Job details
Role: Senior Data Engineer Type: Contract Location: Remote - Canada Required Skills: Data-AWS Glue with EMR, Spark, Redshift, Kinesis, S3, AWS Native Data Services. Position Summary The Senior Data Engineer leads complex data engineering projects and designs data architectures that align with business requirements. This role focuses on optimizing data workflows, managing data pipelines, and ensuring the smooth operation of data systems. Responsibilities Lead development of data pipelines and architectures that handle large-scale data sets. Design, construct, and test data architecture aligned with business requirements. Provide technical leadership for data projects, ensuring best practices and high-quality data solutions. Collaborate with product, finance, and other business units to ensure data pipelines meet business requirements. Oversee development of data solutions that enable predictive and prescriptive analytics. Ensure the technical quality of solutions, managing data as it moves across environments. Align data architecture to Healthfirst solution architecture. Minimum Qualifications / Experience 8+ years of overall IT experience Minimum 5 years of work experience in the tech skills listed below Technical Skills Strong experience in Python scripting and PySpark for data processing Proficiency in SQL, including big data processing Proven experience in data processing for a data lake in Iceberg format, with a strong understanding of the architecture Experience with AWS Glue jobs Experience with the AWS cloud platform and its data services: S3, Redshift, Lambda, EMR, Airflow, Postgres, SNS, EventBridge Expertise in Bash/Shell scripting Domain & Leadership Strong understanding of healthcare finance systems Experience leading data engineering teams Experience in Agile environments Soft Skills Excellent problem-solving skills and attention to detail Effective communication and collaboration skills.
What you’ll do
Lead the design, development, testing, and optimization of large-scale data pipelines and architectures aligned with business and solution architecture requirements. Provide technical leadership, collaborate with business teams, and oversee high-quality data solutions that support predictive and prescriptive analytics.
Requirements
Requires at least 8 years of overall IT experience and 5 years of experience with relevant technical skills, including Python, PySpark, SQL, AWS data services, and data lake processing with Iceberg. Candidates should also have healthcare finance domain knowledge, experience leading data engineering teams in Agile environments, and strong problem-solving, communication, and collaboration skills.
Listed skills
- SQL · Preferred
- PostgreSQL · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- PySpark
- SQL
- Apache Iceberg
- AWS Glue
- Amazon S3
- Amazon Redshift
- Amazon EMR
- Amazon Kinesis
- AWS Lambda
- Apache Airflow
- PostgreSQL
- Amazon SNS
- Amazon EventBridge
- Bash/Shell Scripting
- Data Pipeline Architecture
Job areas
- Data & Analytics
- Technology
- Software
- Healthcare
- Management & Leadership