Analytics Engineer
Job Summary
Job Description
As an Analytics Engineer at Miniclip, you will collaborate with business stakeholders to translate requirements into clean, accurate data models, empowering users to answer their own questions. You will bridge the gap between data analysts, scientists, and engineers, transforming raw data into effective models and products while ensuring data quality. You will also build and maintain efficient data pipelines using tools like dbt, implementing software development best practices, and staying updated with emerging analytics and data engineering technologies.
Must have:
- Collaborate with business stakeholders to collect business requirements and translate them into data models.
- Provide clean, accurate datasets to empower other users.
- Work closely with data analysts and data scientists to understand their analytical needs.
- Collaborate with data engineers to transform raw data into effective data models and products.
- Ensure data quality and availability throughout the process.
- Develop and implement efficient data pipelines using tools like dbt.
- Automate data transformation and empower analysts.
- Implement best practices of software development in data workflows.
- Continuously learn and stay up-to-date with emerging trends and technologies.
Good to have:
- Experience of Python scripting.
- Experience with Data Vault.
- Experience with open format tables such as Iceberg or Delta.
- Experience with Apache Spark or Databricks.
- Experience with IaC tools such as Terraform or Cloud Formation.
- Building and maintaining DAGs in Airflow.
9 skills required
Job Details
Description
What will you be doing at Miniclip?
As an you will be expected to:
- Collaborate with business stakeholders: Collect business requirements and translate them into data models that provide clean, accurate datasets. This empowers other users within the company to become more autonomous in answering their own questions.
- Bridge the data gap: Work closely with data analysts and data scientists to understand their analytical needs and collaborate with data engineers to transform raw data into effective data models and products. Ensure data quality and availability throughout the process.
- Build and maintain data model workflow: Develop and implement efficient data pipelines using tools like dbt (or similar EL T tools) to automate data transformation and empower analysts. Implement best practices of software development in data workflows.
- Be tech savvy: Continuously learn and stay up-to-date with emerging trends and technologies in the analytics and data engineering world.
What are we looking for?
We are looking for a team player who is passionate about games. The ideal candidate should be skilled in the following areas:
- Experience with SQL data querying and manipulation. Experience of Python scripting is a plus.
- Experience in designing, implementing, maintaining and extending Kimball dimensional models. Data Vault is a plus.
- Familiarity with a data transformation tool like dbt core or dbt Cloud (or similar
transformation tools).
- Experience with data warehousing in tools such as Redshift, BigQuery or Snowflake.
- Experience with open format tables such as Iceberg or Delta is a plus.
- Experience with orchestration tools like Airflow. Building and maintaining DAGs is a plus.
- Experience with Apache Spark or Databricks is a plus.
- Experience with cloud-based data platforms such as AWS, Azure or GCP .
- Experience with IaC tools such as Terraform or Cloud Formation is a plus.
- Excellent communication and interpersonal skills to work effectively with both technical and non-technical teams.
- Strong analytical skills and passion for tackling data challenges with innovative solutions.
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