Design, develop and maintain scalable and reliable data engineering pipelines to support analytics and business intelligence needs
Architect, design and implement solutions that meet stakeholders needs
Architect, implement and optimize Snowflake data warehouse solutions including data modeling, performance tuning and cost optimization
Lead and support data migration initiatives including migration from on-premises or legacy data platforms to Snowflake or other cloud based solutions
Develop and manage ELT/ETL processes using modern data integration tools and frameworks
Participate actively in requirements gathering, data modeling and design sessions
Prepare high-level and detailed technical specifications for the projects in accordance with security and architecture documentation objectives
Develop detailed plans and accurate estimates for the completion of the build, system testing and implementation phases of a project
Collaborate with data architects, analytics teams and business stakeholders to translate requirements into technical solutions
Running and optimizing SQL queries on RDBMS like MS SQL server, MySQL, MariaDB
Ensure data quality, security, governance and compliance throughout the data lifecycle
Develop code, document and execute unit tests, systems integration, and acceptance tests and testing tools for functions of high complexity
Troubleshoot and resolve performance, data integrity and pipeline reliability issues
Document architecture, data flows and operational procedures

Strong hands-on experience in Data Engineering including data pipeline development and largescale data processing
Deep expertise in Snowflake architecture including Virtual warehouses, Micro partitioning, Clustering and performance optimization, Security and access control
Proven experience with data migration projects including assessment, planning, execution and validation
Minimum 5 years of experience in software engineering or analytics in creating enterprise data architectures, distributed and microservice software architectures and design patterns
Strong SQL skills and experience with data modeling, dimensional and or data vault
Core SQL database concepts including creating DDL, DML scripts, normalization, running and optimizing SQL queries on RDBMS
Experience working with cloud platforms (AWS, Azure or GCP)
2 years of application development experience in Hadoop, NoSQL databases like MongoDB, Cassandra or HBase
Familiarity with orchestration and data integration tools (e.g., Airflow, dbt, Informatica, Fivetran or similar)
Prior experience with Liquibase, Git, code repos (like GitHub)
Bachelor's degree in Information Technology or Computer Science
Strong problem-solving skills and ability to work independently in a fast paced environment.

Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
Company paid holidays
Personal Days
Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

Data Engineer

Key skills