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Data-Driven Analytics Specialist

2 months ago

Melbourne, Victoria, Australia Deputy Full time
About Deputy

Deputy is a global SaaS workforce management company that empowers businesses to build thriving workplaces. Our mission is to enable businesses to serve their customers well, maintain legal compliance, and drive profits.

The Role

This role bridges analytics and data engineering, bringing software engineering expertise to a team of business-focused analysts and data scientists. As an Analytics Engineer, you will be responsible for productionizing data applications, such as forecasting and attribution models, and expanding our architecture for the data warehouse, BI tools, and machine learning use cases.

Responsibilities
  • Design and optimize data pipelines and architectures using Databricks Data Warehouse to ensure scalability and reliability for large data volumes.
  • Collaborate with Data Engineering to build infrastructure for data extraction, transformation, and loading using SQL and AWS big data technologies.
  • Utilize dbt to create and maintain efficient data models, transforming raw data into actionable insights for key stakeholders.
  • Develop advanced analytics solutions, including machine learning models and predictive analytics, to support data-driven decision-making.
  • Work closely with cross-functional teams, including Data Scientists, Engineers, and Product Managers, to deliver data solutions that align with business objectives.
  • Establish best practices for data quality, governance, and security to maintain the integrity of our data assets.
  • Provide mentorship and share expertise on analytics and data engineering best practices with team members.
  • Stay informed on emerging technologies and techniques in data engineering and analytics to drive innovation.
  • Advocate for data-driven decision-making by promoting the value of data across teams and fostering collaboration.
Requirements
  • 2-3 years of experience in a technical analytics or data engineering role, with a strong background in Computer Science, Information Systems, or a related field.
  • Expertise in SQL and relational databases, with experience working on data modeling and query authoring.
  • Skilled in using dbt for data modeling and transformation, with a focus on building efficient data pipelines.
  • Experience in applying advanced analytics techniques, such as machine learning and predictive modeling, to real-world challenges.
  • Proficiency in using analytical tools and libraries like Pandas, NumPy, and Scikit-learn for data analysis and model development.
  • Working knowledge of stream processing and scalable data stores.
  • Solid understanding of data management principles, governance best practices, and regulatory requirements.
  • Ability to communicate technical insights to non-technical stakeholders, driving alignment on data initiatives.