Sr. Data Solutions Architect
New
CanadaFull-TimeSenior
Salary170000 - 180000 CAD per year
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Job Details
- Experience
- 7+ years
- Required Skills
- PostgreSQLPythonDynamoDBETLJavaKafkaMongoDBMySQLSnowflakeAzureCassandraScalaDatabricksMLOps
Requirements
- 7+ years of experience in public cloud environments (Azure preferred) with strong data engineering and architecture exposure.
- 5+ years of hands-on development experience using Python, Java, or Scala.
- Strong experience building ETL/ELT pipelines, data processing systems, and distributed data architectures.
- Expertise in designing and implementing data lakes, data warehouses, and analytics platforms using tools such as Snowflake, Databricks, or Microsoft Fabric.
- Experience with relational and NoSQL databases, including systems such as PostgreSQL, MySQL, MongoDB, Cassandra, or DynamoDB.
- Proven experience in streaming and real-time data systems using technologies like Kafka, Kinesis, Pub/Sub, or Spark Streaming.
- Strong understanding of AI/ML solution design, MLOps, and model deployment pipelines.
- Consulting experience with client-facing delivery, technical leadership, and stakeholder management.
- Strong communication, documentation, and presentation skills with the ability to influence technical and business audiences.
- Knowledge of data governance, security, compliance frameworks (e.g., GDPR, HIPAA, PCI), and data lifecycle management.
Responsibilities
- Lead end-to-end design and implementation of enterprise-grade data platforms, including data lakes, warehouses, and analytics ecosystems.
- Act as technical authority across engagements, guiding architecture decisions, tool selection, and resolution of complex engineering challenges.
- Lead data engineering teams, providing technical direction, task breakdown, prioritization, and mentorship throughout project delivery.
- Facilitate architecture workshops and whiteboard sessions with clients and internal stakeholders to define requirements and solution approaches.
- Design and oversee ETL/ELT pipelines, real-time streaming systems, and large-scale batch processing architectures.
- Develop and integrate AI/ML solutions, including model training, optimization, and MLOps lifecycle automation.
- Ensure governance across data systems, including security, compliance, privacy, lifecycle management, and cost optimization.
- Manage project scope, risks, and deliverables while maintaining strong client relationships as a trusted technical advisor.
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