The Role
The Data and Analytics Engineer is a hands-on technical role developing and maintaining the Azure data warehouse environment, delivering data engineering, data warehousing and analytical report development. The role will also working on other ETL applications and data warehousing functions as needed to enhance and maintain all data used by the company.
Key Responsibilities
- Responsible for building data integrations, pipeline orchestrations, and data warehouse platforms
- Responsible for data documentations, data definitions, reports and visualisations
- Responsible for providing clean and accurate data to the business
- Responsible for the development and design of technical solutions relating to data and integrations
- Supports the team in creating data assets used for reporting and visualization.
- Supports the team and various departments in building and developing data integrations and reports.
- Working with business and technical stakeholders to understand requirements relating to data and analytics initiatives with a focus on delivering business outcomes
- Responsible for designing, developing, testing, documenting, and maintaining data models, reports, and dashboards that meet business needs and requirements
- Designing, developing, testing, documenting, and maintaining data pipelines across a range of technologies that extract, load, combine and transform data from a range of internal and external sources
- Understand and implement data governance requirements that support data and analytics solutions including security, data quality, data classification, trustworthiness, and re-usability
- Collaborating with technical and non-technical stakeholders through a range of forums including but not limited to team members within cross functional delivery teams, data and analytics practice group, and the data and analytics platform team.
Experience & Knowledge
- Three plus years experience in data engineering, data modelling, data warehouse development in cloud environments
- Proficiency in T-SQL, SQL Server, Databricks, PySpark, SSRS, Power BI, Data and dimensional modelling and other related data tools and platforms
- Experience in building and optimizing data pipelines, data models, reports, and dashboards
- Skills and experience ingesting data from various external sources including RDMS (SQL Server, Postgres), SaaS service via RESTful web services, Event sources such as Azure Event Hub, Kafka, and Webhooks
- A broad technical understanding of Information Technology
- Exposure to both on premises and cloud-based platforms
- Excellent verbal and written communication skills, including the ability to capture and explain goals and objectives to business as well as technical leadership.
- Excellent analytical, collaboration and facilitation skills