Company Overview
Teranet is Canada’s leader in the delivery and transformation of statutory registry services, with extensive expertise in land and commercial registries. Our unmatched registry expertise makes us the most authoritative source of data and market insight for the financial services, real estate, and government and utility sectors. Through our global partnership with Foster Moore, Teranet has expanded its registry solutions to include commercial-off-the-shelf (COTS) registry technology that delivers operational cost reductions, enhanced security and process improvements. Teranet is owned by OMERS Infrastructure, a leading global infrastructure investment manager and the infrastructure arm of the Ontario Municipal Employee Retirement System. As a pioneer in electronic registration systems and commerce, Teranet has received numerous awards for our technology platforms, expertise and our successful partnerships with the Provinces of Ontario and Manitoba.
About the job
Senior Data Analyst
Who We Are
Teranet is Canada’s leader in the delivery and transformation of statutory registry services with extensive expertise in land and commercial registries. We also market insightful property and data solutions, as well as practice management automation to thousands of customers in the real estate, financial services, government, utilities, and legal markets.
About the Role
Teranet is currently looking for a Senior Data Analyst.The Data & Analytics team within the Commercial Solutions line of business has an ambitious mandate, where we are accountable for leveraging Data & Analytics to deliver business value both internally as well as to external clients through the following:
Enhance existing or create new products and services with proprietary data assets and partnering with external data providers, through the application of data science.
Design and deliver cutting-edge reporting solutions to bring data to life.
Conduct advanced data analysis to generate business insights that drive strategic decision-making.
Demonstrate thought leadership in the ecosystem in which we operate.
Provide actionable recommendations to improve overall organizational efficiencies.
In addition, this team will play an important role in evangelizing and educating of the value of Data & Analytics to the rest of the organization, in support of cultivating a data-driven culture.
The Senior Data Analyst will support these ambitious goals primarily through ensuring seamless data integration, maintaining high quality data standards, collaborating with cross functional teams, and delivering comprehensive analyses and innovative visualization using business intelligence tools.
What You’ll Be Doing
The Senior Data Analyst supports the team in the design, development, and implementation of data & analytics use cases through the following responsibilities:
Business Data Consultation (35%)
Engage with stakeholders to understand business requirements and objectives for data & analytics use cases.
Translate business questions into technical data needs, ensuring alignment with project goals.
Research, identify and then collect / extract the external data sets required for the use case. Creativity, thinking outside of the box, and resourcefulness is required to find new and relevant data sources to meet business requirements.
Exhibit a strong attention to detail while working with large datasets to ensure accuracy, completeness, and high-quality standards.
Translate technical findings into clear recommendations for non-technical stakeholders, ensuring alignment with business use case.
Data Processing and Engineering Support (30%)
Partner with data engineers and data scientists to ensure data pipelines and models align with organizational goal.
Analyze, assess, and remedy the data for quality and usability.
Recommend ways to integrate disparate data sources into a usable data model to meet business requirements.
Present business insights in a meaningful and intuitive manner, in accordance with the target audience, using visualization or BI tools.
Data Analytics and Visualization (35%)
Implement category and segmentation techniques and create dynamic data solutions tailored to stakeholder needs.
Demonstrate curiosity by exploring datasets, conducting exploratory data analysis to uncover hidden trends, outliers, anomalies, and identify insights that might not be obvious.
Provide detailed analysis of customer behavior, market trends, and competitive landscape to support product, sales and marketing strategies.
Design and deliver advanced data visualizations and dashboards to convert large datasets into compelling storyline.
About You
What will you need to be successful?
You are someone who:
Is keen to understand the business – data analytics cannot be done in a vacuum – we need to be close to the business so that we understand what we are trying to solve for and what the data means.
Tells stories from data – data analytics is not data dump – it needs to be meaningful and intuitive to the end user to realize the inherent business value.
Challenges the status quo – the state of business and the field of data analytics are constantly evolving, and we need to as well. Assumptions and old ways of doing things are open season, as long as you bring along workable and relevant solutions articulated in a professional manner. Proactively pursue and learn about new data sets, analytical tools, and methodologies to solve problems in new and innovative ways.
Is good at problem solving – someone who can “connect the dots”, and have a logical and methodical way to tackle new and complex problems.
Takes pride in your work – your work is diligent and thorough and you are proud of your reputation for high-quality and reliable work.
Is a quick study – the successful candidate must be curious, resourceful, and dig into the weeds to ask the right questions and figure things out independently.
Is a good communicator – someone who is polished and can communicate effectively with internal and external parties to ensure alignment on data analysis and reporting needs.
Technical qualifications:
Bachelor’s degree in a quantitative field: Statistics, Mathematics, Computer Science, Engineering
Minimum 5 years of work experience in a Data Analyst or Senior Data Analyst capacity
Proficiency in SQL and Python (regular usage, practical experience)
Practical experience in data analysis: data cleansing, exploration, and modelling
Proficiency in using data visualization tools (Tableau), other BI tools (PowerBI), and Excel
Knowledge of Big Data Technologies: Hadoop, HDFS, Hive, HBase, Storm, Spark, Kafka, etc. Proficiency in cloud technologies such as AWS and Azure for data processing, and analytics
Understanding of spatial data concepts, including geospatial data formats (e.g., GeoJSON, Shapefiles), spatial analysis, and tools like ArcGIS
How to Apply:
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