Who You Are :

As a seasoned Data Engineer specializing in data engineering, you bring extensive expertise in optimizing data workflows using various database tools like Oracle, BigQuery, and SQL Server.

You possess a deep understanding of ELT/ETL processes, data integration, and have a strong command of Python for data manipulation and automation tasks.

You will possess advanced expertise in working with data platforms like Google Big Query, DBT, Python, and Airflow.

Responsible for designing and maintaining scalable ETL pipelines, optimizing complex data systems, and ensuring smooth data flow across different platforms.

As a Senior Data Engineer, you will also be required to work collaboratively in a team and contribute to building data infrastructure that drives business insights.

What Youll Do :

- Design, develop, and optimize complex ETL pipelines that integrate large data sets from various sources.

- Build and maintain high-performance data models using Google BigQuery and DBT for data transformation.

- Develop Python scripts for data ingestion, transformation, and automation.

- Implement and manage data workflows using Apache Airflow for scheduling and orchestration.

- Collaborate with data scientists, analysts, and other stakeholders to ensure data availability, reliability, and performance.

- Troubleshoot and optimize data systems, identifying issues and resolving them proactively.

- Work on cloud-based platforms, particularly AWS, to leverage scalability and storage options for data pipelines.

- Ensure data integrity, consistency, and security across systems.

- Take ownership of end-to-end data engineering tasks while mentoring junior team members.

- Continuously improve processes and technologies for more efficient data processing and delivery.

- Act as a key contributor to developing and supporting complex data architectures.

What Youll Need :

- Bachelors degree in computer science, Information Technology, or a related field.

- 4+ years of hands-on experience in Data Engineering or related fields, with a strong background in building and optimizing data pipelines.

- Strong proficiency in Google Big Query, including designing and optimizing queries or other equivalent Datawarehouse (Snowflake).

- Knowledge of dbt for data transformation and model management.

- Proficiency in Python for data engineering tasks, including scripting, data manipulation, and automation.

- Solid experience with Apache Airflow for workflow orchestration and task automation.

- Extensive experience in building and maintaining ETL pipelines.

- Familiarity with cloud platforms, particularly AWS (Amazon Web Services), including tools like S3, Lambda, Redshift, or Glue.

- Excellent problem-solving and troubleshooting abilities.

- Strong communication and collaboration skills with the ability to work effectively in a team environment.

- Self-motivated, detail-oriented, and able to work with minimal supervision.

- Ability to manage multiple priorities and deadlines in a fast-paced environment.

- Experience with other cloud platforms (e.g., AWS, Azure) is a plus.

- Knowledge of data warehousing best practices and architecture.

WHATS IN IT FOR YOU?

At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done.

Apply by completing the online application on the careers section of our website.

We are an Equal Opportunity employer committed to a diverse workforce.

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.