Data Engineer

Job Description

As part of the Adrenaline team, join our team and drive the development of our data products that align with our business objectives. You will collaborate with cross-functional teams, including leadership, architects, analysts, product management, project management, and data scientists, to understand and address data requirements effectively. You will report to the Director of Data Architecture.

What you will do:
• Collaborate with cross-functional stakeholders, including analyst, governance, project management, and data scientists, to comprehend data needs and ensure alignment with business goals.
• Design, build, and launch efficient and reliable data pipelines to move and transform data effectively, handling both large and small amounts.
• Possessing the capability to interpret and construct code, as well as provide insightful feedback during code reviews, focusing on elements such as scalability, performance, and adherence to best practices.
• Ensure scalability and efficiency by designing and implementing complex features, including multi-layered data workflows.
• Deploy data quality checks in collaboration with quality engineering and data governance teams to uphold high-quality data standards.
• Uphold a high-quality code base by writing and reviewing performant, scalable, and well-tested code to deploy effectively using source control products such as GitLab/GitHub.
• Define and manage SLAs for all data sets in allocated areas of ownership.
• Utilize job scheduling tools like Airflow and GitLab Runners to streamline processes.
• Maintain data engineering and architecture best practices and standards within the team and the wider organization, fostering a culture of quality, innovation, and experimentation.
• Take ownership of the end-to-end data engineering component of the product.
• Identify, design, and implement internal process improvements in collaboration with data architects, including automating manual processes and optimizing data delivery.
• Create and maintain technical documentation.

Qualifications:
• BS/MS in Computer Science, Engineering, or a related field with 8+ years of data engineering experience.
• A must experience with Snowflake, Git, DBT & Airflow
• 7+ years of experience in ETL orchestration and workflow management tools.
• Experience using containerization technologies such as Docker or Kubernetes.
• Proficiency in programming languages such as Python (preferred) & SQL
• Strong understanding of data modeling, warehousing, and building ETL/ELT/EtLT pipelines.
• Knowledge or Experience in Data mesh and Data Lake House Designs.
• Excellent written and verbal communication skills, ability to simplify and synthesize complex constructs.

COMPENSATION AND BENEFITS The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs). BASE SALARY RANGES
• British Columbia (depending on location e.g. Vancouver vs. Victoria)
• $115,100 - $161,200 CAD

In British Columbia, we offer a package of benefits including vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and equity.

Jobcode: Reference SBJ-rep5m2-3-15-144-162-42 in your application.