Senior Data Engineer

Roles and Responsibilities:

• Data Pipeline Development: Design, build, and maintain robust and scalable ETL/ELT pipelines using tools like Informatica, Airflow, and Dataproc.
• Data Warehousing: Develop and manage our data warehouse on Google BigQuery, ensuring data is accurate, available, and easily accessible.
• Data Processing: Utilize Databricks and Python to process and transform large volumes of data efficiently.
• DevOps & Automation: Implement and manage CI/CD pipelines for data workflows using DevOps best practices and tools like Dataform and GitHub.
• Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand their data needs and provide them with high-quality data.
• Data Modeling & BI (Optional): Develop data models and support BI initiatives by creating dashboards and reports in tools like Tableau.
• EPM Integration (Optional): Integrate data with our Anaplan platform to support connected financial and operational business planning.

Required Skills and Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of proven experience in a data engineering role.
• Strong proficiency in SQL and extensive experience with Google BigQuery.
• Hands-on experience with big data technologies such as Databricks and Dataproc.
• Experience with ETL/ELT tools like Informatica.
• Proficiency in orchestrating data pipelines with Airflow.
• Strong programming skills in Python.
• Solid understanding of DevOps principles and experience with Dataform and GitHub for CI/CD and version control.

Preferred Qualifications:

• Experience with BI visualization tools, particularly Tableau.
• Familiarity with EPM tools, especially Anaplan.
• Relevant certifications in Google Cloud Platform (GCP) or other data technologies.
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.