Data Infrastructure Lead

2 months ago


Edmonton, Canada Government of Alberta Full time

**Job Information**:
Job Requisition ID: 46795

Ministry: Advanced Education

Location: Edmonton

Full or Part-Time: Full Time

Hours of Work: 36.25 hours per week

Regular/Temporary: Regular

Scope: Open Competition

Closing Date: August 28, 2023

Classification: Subsidiary 02B 3625 Program Services 4

**About Us**:
The Data Management and Governance (DMG) unit aims to improve the ministry’s data maturity, as follows:

- Develop, implement, and evolve and enterprise-wide data management and governance.
- Develop, implement, and evolve stewardship of the Department's major administrative datasets.
- Collect and provide oversight of key administrative data from the advanced learning system.

**Role**:
**Do you geek out about great data infrastructure? Does your curiosity drive you to the underlying problem? Are you keen to build up capacity in your colleagues? This opportunity may be for you**

Reporting to the Manager-Data Management, you will build data infrastructure to enable new digital services and business intelligence. This includes developing and optimizing pipelines, data warehouse and orchestration platforms, and cloud storage to reliably move data from multiple source systems, assessing existing infrastructure, and developing a roadmap for infrastructure improvement.

Your technical acumen, teaching skills, and listening attitude will help the DMG unit improve Advanced Education’s data management and governance capacity.

**Responsibilities**

**1. Build data infrastructure to meet AE's operational and analytic needs.**
- Build data pipelines from one or more sources to cloud storage and data warehouse in a customized way, including orchestration, masking, testing, reviewing, troubleshooting, scheduling, and documenting.
- Leverage replication tools (Nexla, Airbyte) to copy data from desperate sources into the centralized data storage location (Azure Blob Storage).
- Organize structured (e.g. postgres tables) and unstructured data (e.g. json) into analyst-friendly tables in the centralized data cloud (Snowflake).
- Develop messaging and alerting systems so that failure and error reporting happen in an automated, trusted way.
- Maintain the tooling libraries that enable automation and quality of the data warehouse: custom operators and scripts for orchestration (based on Astronomer/Airflow), continuous integration and deployment (CircleCI), code deployment process, and linting. Enable analysts and modellers to work effectively by supporting the tools they use, including Data Build Tool (DBT) for data transformations inside the centralized data cloud.**2. Implement best practices to guide infrastructure development and planning.**
- Own and drive AE's data infrastructure building standards, developing documentation and processes to support junior and future data infrastructure staff in the unit.
- Identify and prioritize building and maintenance work, taking in to account department business priorities, technical dependencies, and unit coordination and capacity.
- Develop and maintain a roadmap for development and improvement of infrastructure and standards.
- Build a library of data infrastructure documentation and resources for unit and Department staff.

**3. Back up data modelling and data reporting functions.**
- Cross train with data modelling and reporting colleagues to ensure business continuity.
- Draft, test, and review data model scripts.
- Develop and maintain data model documentation including standards.
- Draft and review reports, visualizations, and dashboards.
- Develop and maintain reporting and visualization documentation including standards.

**Qualifications**:
**Requirements**:
A University Degree in Computer Science, Data Science, Statistics, informatics or related field and minimum of 4 years related experience. Directly related experience or education considered as an equivalency on a one-for-one basis.

**Equivalency**: Directly related education or experience considered on the basis of:

- 1 year of education for 1 year of experience; or
- 1 year of experience for 1 year of education

The Data Infrastructure Lead must have at least four years of experience performing the following work:

- Optimizing data infrastructure/data pipeline architecture and building these structures from the ground up, including optimizing data flow and collection for cross-functional teams.
- Collaborating with teams of data analysts, data scientists, and software developers on data initiatives.

Related experience or education may be considered as an equivalency on a one-for-one basis.
- To be successful in this job, you need_
- A deep knowledge of data scripting languages Python, Data Build Tool (DBT), and Linux.
- Significant experience using version control systems (Github): branching, writing and saving code, creating pull requests, doing pull requests for code reviews, etc.
- Knowledge of orchestration (Airflow and Astronomer), cloud hosting and storage (Azure Blob Storage), and cloud



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