Senior Data Analytics Engineer

Summary

Join Paddle as a Senior Data Engineer and contribute to our data strategy by delivering technical solutions. You will build and maintain data pipelines, develop data models for self-service analytics, and collaborate with cross-functional teams. This role requires expertise in SQL, data modeling, and various data engineering tools and technologies. You will ensure data accuracy and implement DevOps practices. Paddle offers a comprehensive benefits package including attractive salaries, stock options, retirement plans, private healthcare, unlimited holidays, enhanced parental leave, and a personal development fund.

Requirements

• Advanced SQL and data modeling skills, including experience with dbt and data warehousing solutions (e.g., Snowflake, BigQuery)
• Good knowledge of database management systems such as SQL, NoSQL, and columnar databases
• Experience working with orchestration frameworks, like Airflow
• Experience with CI/CD pipelines in a data engineering context, applying version control, testing, and automation best practices
• Experience with cloud-based platforms such as AWS, GCP, or Azure
• Experience with data integration tools like Fivetran, Meltano, Airbyte, Stitch, or similar
• Strong attention to detail to identify and resolve data quality issues
• Strong collaboration and communication skills to work effectively with cross-functional teams and convey complex data concepts to diverse stakeholders

Responsibilities

• Build and maintain efficient, secure data pipelines to ensure smooth data flow across the organization
• Develop and maintain data models to enable self-service analytics, supporting consistent, accurate reporting and data governance
• Collaborate with cross-functional teams to understand data requirements and develop solutions that meet both immediate and long-term business needs
• Assist internal teams with operational data support requests, ensuring they have reliable, timely access to the data they need
• Use various techniques, including advanced aggregations and data wrangling methods, to transform raw data into analytics-ready, well-documented, and highly maintainable datasets that empower data-driven decision-making
• Ensure data accuracy, completeness, and consistency by implementing quality checks and resolving issues proactively
• Implement DevOps practices to deploy and maintain code in production environments
• Stay up-to-date with the latest industry trends, tools, and technologies related to data engineering

Preferred Qualifications

Familiarity with BI tools such as Looker, Tableau, Sisense, or comparable

Benefits

• Attractive salaries
• Stock options
• Retirement plans
• Private healthcare
• Well-being initiatives
• Remote work
• Unlimited holidays
• Enhanced parental leave
• Annual learning fund
• Regular internal and external training