Data Analytics Specialist

3 weeks ago

Halton, Canada Halton Region Full time

**Data Analytics Specialist**:
At Halton Region, we treat everyone with respect, honesty, fairness and trust. As an equal opportunity employer, we are committed to establishing a qualified workforce that is reflective of the diverse population we serve. Halton Region is committed to providing accommodation to individuals with disabilities throughout the recruitment process.

Over the next 4 years, the Region’s goal is to become a Digital First organization that is committed to delivering high-quality services in the digital age. Our Digital Mission is to offer 125 of our most used customer-facing services and the top 50 internal processes and staff experiences as complete digital services by 2025.

Through collaboration, innovation, digital and information decision-making models, accountability, and partnerships, Halton Region aims to Build a Strong Digital Culture. The Region aims to invest in education, and training, celebrate and showcase successes and build a community of practice that will share knowledge and tap into individual skills.

There is no better time to join Halton Region as we transform our conventions and practices to better serve our community and employees.

As an employer of choice, Halton Region recognizes the many benefits of hybrid work arrangements including flexibility and better work-life balance for our employees. This position is eligible for our Hybrid Work Program.

**Posting ID**: 2025
**Department**:Digital & Information Services
**Division**: Digital Services & Data Management
**Pay Range**:$83,686 - $111,577

**Job Type**: Permanent
**Hours of Work**: 35 hours per week
**Work Location**:Halton Regional Centre - 1151 Bronte Road, Oakville
**Employee Group**: OCT
**Posting Date**:June 1, 2023
**Application Deadline**:June 18, 2023

**Job Summary**:
Reporting to the Manager, Data and Information Management within the Digital Services and Data Management division, this position is responsible for implementing and operating data services to collect, manage, integrate, share and reuse high quality data to inform strategic decisions and support the delivery of Halton’s Digital strategic priorities.

**Duties & Responsibilities**:

- Design, develop, and maintain scalable and robust data pipelines to combine, transform, and move large volumes of data from multiple sources to appropriate databases and data warehouses.
- Collaborate closely with analysts and stakeholders to identify, understand, and fulfill data requirements for current and future business needs.
- Ensure high-quality data by implementing strict data validation and monitoring processes, as well as data cleansing and enrichment techniques.
- Troubleshoot and resolve data-related issues, ensuring the efficient flow of information across the data ecosystem.
- Designing, delivering and maintaining enterprise-wide / in-production analytic solutions.
- Developing, evaluating and refining analytic models to inform strategic decision making through data visualization, business intelligence and predictive analytics services.
- Extracting, transforming and analyzing data from multiple data sources, ensuring data quality and integrity is maintained from source to the final output.
- Developing and maintaining a data catalogue identifying what Halton collects and creates and how it is used.
- Developing, maintaining, and enhancing metadata used by both technical and business teams through data quality assessments.
- Identifying areas for data quality improvements and supporting business in developing solutions to systematically resolve issues.
- Other duties as assignment.

**Skills & Qualifications**:
**Essential**
- Degree in Statistics, Economics, Mathematics, Computer Science, Data Science, Business Administration or a related field
- Five (5) years of proven experience in developing data analytic and business intelligence solutions using on premise and cloud-based big data that is structured and un-structured.
- Ability to build scalable and robust data pipelines to combine, transform, and move large volumes of data from multiple sources
- Data extraction, cleaning, collection, organization, analysis and interpretation from various systems
- Understanding of extract, transform, and load (ETL) methodologies
- Database principles and structure, including strong SQL skills for querying data and managing databases
- Understanding of cloud technologies, such as Azure or AWS
- Experience in SAP, Siebel, Hansen/Infor IPS, Salesforce, GIS solutions, MuleSoft and similar enterprise systems in the context of reporting and data extraction.
- Knowledge of data analysis concepts and data mining techniques to present hidden relationships and patterns found within structured and unstructured data sets.
- Proficient in data analytics, engineering, and general purpose programming using languages such as Python.
- Experience with data warehousing/databricks, business intelligence tools and platforms including cloud, on premise and hybri

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