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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;