Analytics Engineer

SkySys; Toronto; On-site; CAD 70,000 - 90,000; Full time

Job summary

A leading analytics company in Canada is seeking an Analytics Engineer to develop and automate data transformation pipelines. The role involves collaborating with various departments, using SQL and Python, and ensuring data integrity. This 6-month contract position offers a dynamic work environment aimed at enhancing decision-making capabilities through data-driven solutions.

Qualifications

• Minimum 3 years of experience as a data analyst, data scientist, analytics engineer, or data engineer.
• Practical experience with SQL and/or Python for data integration.
• Proficiency in data visualization tools such as Tableau or Domo.

Responsibilities

• Develop and automate data transformation pipelines.
• Support analytics platforms while enhancing data foundation.
• Translate business requirements into data models.

Skills

SQL

Python

Collaboration

Data Modeling

Communication

Education

Bachelor's Degree in a quantitative field

Tools

Data Visualization Tools

Git

Airflow

Job description

Position Type : Full-Time Contract (40hrs / week)

Contract Duration : 6 months+ (Possibility of Contract to Hire)

Work Schedule : 8 hours / day (Mon-Fri)

The ideal candidate will develop and automate data transformation pipelines integrating data sources from various parts of the business to drive customer understanding and operational efficiency. As a member of the analytics team, your role will influence the tech stack and frameworks we develop across the organization. As an Analytics Engineer , you will collaborate with departments across the company, including Marketing, Sales, Digital, Supply Chain, and eCommerce. In addition to building data transformation pipelines, your responsibilities will include supporting the development, maintenance, and operational stability of data engineering and analytics infrastructure.

Responsibilities :

• Use SQL and Python to write production-quality code to meet the data transformation needs of analysts, data scientists, and other business partners
• Support the use of analytics platforms and data science workflows, while identifying ways to strengthen and scale our data foundation
• Help design and develop transparent ELT pipelines that deliver timely and accurate data to end users
• Translate business requirements and logic into well-documented data models to drive clarity and efficiency for end users
• Collaborate cross functionally to understand and identify data needs and opportunities to use data to drive business solutions
• Communicate technical concepts to a non-technical audience in a compelling manner
• Evaluate external partners across different dimensions for analytics initiatives
• Partner with IT to align on data architecture, analytics tools, and other technologies

Required Qualifications :

• Bachelor's Degree in a quantitative field
• At least 3 years of professional experience as a data analyst, data scientist, analytics engineer, or data engineer
• Demonstrated proficiency in the use of SQL and / or Python to wrangle, clean, and integrate data from a variety of sources
• Demonstrated understanding of modern data warehouse design principles and data engineering best practices
• Practical experience using data visualization and / or BI tools (e.g., Domo, Tableau) to analyze data
• A commercially astute individual, with the ability to build strong cross-functional relationships. Eager at the prospect of developing and implementing new tools and processes that add organizational value & improve decision making capabilities.
• A bright, ambitious person, with strategic capabilities, able to lead change, influence and collaborate both internally and externally, and with a clear commitment to delivering business results in a timely manner.

Preferred Qualifications :

• Master's or PhD in a quantitative field
• Demonstrated understanding of marketing analytics concepts, including marketing mix modeling, churn risk prediction, and customer lifetime value
• Demonstrated experience with Git / GitHub, dbt Core / Cloud, and Airflow
• Familiarity with SAP systems (ECC, C4C, S4 HANA)