Data Engineer

Join a leading U.S.-based technology platform for the life insurance and annuities industry. Through innovative enterprise solutions and data-driven insights, the company simplifies how insurance products are bought, sold, and administered, helping millions of people protect their financial futures.

With a bold, collaborative, and value-driven culture, the company manages hundreds of billions of dollars in assets under administration and partners with more than 100 insurance carriers and thousands of distributors across the market.

Responsibilities

• 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/ Snowflake 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, identify issues, and resolve 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.
  

Requirements

• Bachelor’s degree in computer science, Information Technology, or 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.

Benefits

• Your pick when it comes to employment models: CLT/PJ/Cooperativa;
• We provide resources for you to grow and learn on the job, including online courses, mentoring, and the latest gen laptops;
• A fully remote work environment with flexible working hours;
• Bonus for any referrals that we end up hiring;