Senior Analytics Engineer - Analytics Engineering - Databricks - Pyspark - Dimensional Modelling
Nexere Consulting Limited
- Industry Type
- Engineering Design, Consulting
- Functional Area
- Engineering
- Nationality
- Any
- Keywords
- PySpark Dimensional Models Analytics Engineering Data Lakehouse
Job Description
Nexere Consulting Limited in Cambridge, United Kingdom, is looking for a Senior Analytics Engineer. The role involves designing and delivering analytics-ready data using PySpark and dimensional modeling within a Lakehouse environment.
- Position
- Senior Analytics Engineer
- Company
- Nexere Consulting Limited
- Location
- Cambridge, United Kingdom
- Industry
- Engineering Design, Consulting
- Experience
- 1 to 20 years
Responsibilities
- Design and deliver curated, analytics-ready data within the Lakehouse environment.
- Translate complex business requirements into scalable solutions using PySpark and dimensional modeling.
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About the role: Senior Analytics Engineer - Analytics Engineering - Databricks - Pyspark - Dimensional Modelling
General information about this type of role, not from the employer. The employer's actual requirements may differ, so always check the job details above.
Senior Analytics Engineers design and develop data analytics solutions to help organizations make informed decisions. They typically work in engineering design, consulting firms, or technology companies, using tools like Databricks and Pyspark to process and model data.
What this role usually involves
- Design and implement data pipelines and analytics workflows.
- Develop dimensional data models to support business intelligence.
- Collaborate with data scientists and business stakeholders to understand requirements.
- Optimize data processing performance using tools like Pyspark and Databricks.
- Ensure data quality and consistency across analytics platforms.
- Document analytics solutions and provide technical guidance to junior team members.
Skills employers usually look for
- Strong programming skills in Pyspark and Python.
- Experience with data modeling, especially dimensional modeling.
- Proficiency in using Databricks or similar big data platforms.
- Ability to analyze complex data sets and derive insights.
- Good communication and collaboration skills.
- Problem-solving and optimization techniques for data processing.
Usual qualifications
- A degree in computer science, engineering, data science, or a related field is usually expected.
- Knowledge of data warehousing and business intelligence concepts.
- Familiarity with cloud-based data platforms and big data technologies.
- Relevant certifications in data engineering or analytics can be advantageous.
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