Analytics Engineer

We are seeking an Analytics Engineer to join our team and play a pivotal role in shaping our analytics infrastructure and processes. You will act as a bridge between raw data management and actionable business insights, ensuring that data is accurate, accessible, and primed for analysis.

Key responsibilities:

Data Integration and Pipeline Development:

• Develop and maintain robust, scalable data pipelines to integrate data from various sources.
• Ensure timely, accurate ETL process
• Evaluate and recommend analytics tools and platforms that best fit the organization's needs.
• Monitor data accuracy, consistency, and completeness, implement new tools if needed
• Identify, rectify, and prevent data quality issues, ensuring data integrity across the analytics landscape.
• Develop and maintain a data governance framework
• Work closely with data scientists, analysts, and business stakeholders
• Oversee the architecture and performance of databases used for analytics.
• Optimize queries, indexes, and data storage for efficient retrieval and analysis.
• Document data pipelines, architectures, and governance policies for transparency and easy reference.
• Train and guide analytics teams on best practices, tools, and methodologies.
• Monitor the performance of data pipelines and databases, ensuring they meet the required service level agreements (SLAs).
• Plan and implement solutions for scaling the analytics infrastructure in line with the organization's growth.
• Implement and monitor security measures to protect sensitive data and prevent unauthorized access.
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Required experience:

• Good knowledge and proven experience of practice SQL
• Good visualisation tools experience. Understanding of their work and what gaps they solved.
  - Redash/Superset/Tableau/Power BI/Google Data Studio.
• Python experience or Scala
• Good knowledge of probability theory and statistics. You should thinks in hypotheses and understands the essence of analytical work.
• Understanding of A/B testing principals and theory
• Demonstrated capacity to clearly and concisely communicate complex business activities, technical requirements, and recommendations
• Demonstrated experience with one or more of the following business subject areas: marketing, finance, sales, product, customer success, customer support, engineering, or people/ML/science
• 3+ years experience designing, implementing, operating, and extending commercial Kimball or other enterprise dimensional models
• 3+ years working with a large-scale (1B+ Rows) Data Warehouse, preferably in a cloud environment
• 2+ years experience in BI