Trinca: Senior Data Engineering

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Overview of the Job

The position is for a Senior Data Engineer at Trinca, a company that invites individuals to build initiatives rather than merely filling vacancies. They emphasize the significance of data as the fundamental element in any crucial decision making. If you have the ability to transform raw data into valuable insights and are seeking a challenging role in a data-intensive sector in Brazil, then this opportunity could be the next big step for your career.

Job Responsibilities

In this role, you will be at the heart of the data journey for an expanding insurance platform that has increasing governance and a real demand for data quality. Your primary function will encompass:

• Building and Evolving Data Infrastructure: You will be tasked with constructing and enhancing the data infrastructure crucial for a large-scale insurance platform, ensuring that the correct information reaches the right people timely.

• Designing and Maintaining Data Pipelines: You will design, implement, and maintain robust, scalable data pipelines that integrate data from APIs, internal systems, and external sources with a focus on volume and reliability.

• Data Architecture and Modeling: You will develop and evolve data models within a Data Lakehouse architecture (specifically Delta Lake) to facilitate complex analysis and support the platform’s growth.

• Orchestration and Automation: There will be responsibilities to set up and operate orchestration tools like Airflow or Dagster to ensure the processes run smoothly and punctually.

• Ensuring Data Quality and Governance: You will be involved in developing a unified data dictionary, applying CI/CD practices to data pipelines, ensuring integrity, and maintaining traceability of data.

• Business Partnerships: Collaborating with product teams, analysts, and data scientists will be a key aspect to convert business questions into actionable analyses, identifying opportunities for improvement.

• Data Innovations: Supporting machine learning initiatives and predictive modeling will be included in your responsibilities, contributing to the anticipation of trends and operational optimizations.

Required Skills and Qualifications

Essential Requirements

• Proven experience in Data Engineering, specifically with a history of building and maintaining robust, scalable data pipelines in high-volume environments.
• Proficient in Databricks and/or other distributed analytical platforms, including familiarity with Data Lakehouse architectures and Delta Lake.
• Advanced proficiency in SQL and mastery of relational as well as non-relational databases (including PostgreSQL, MongoDB, and Cassandra).
• Strong capabilities in Python with PySpark and significant experience utilizing Big Data frameworks such as Apache Spark or Apache Flink.
• Familiarity with orchestration tools such as Apache Airflow or Dagster.
• Experience with cloud environments (like Azure, AWS, or GCP) and distributed storage services (e.g., Azure Data Lake Storage, AWS S3, GCS).
• Understanding of CI/CD practices and version control using Git/GitHub applied to data pipelines.
• Real-world application of AI in projects, demonstrating tangible use cases where AI was utilized to improve speed, quality, or consistency in data engineering.

Preferred Qualifications

• Experience with Business Intelligence tools like Power BI, Tableau, or Looker for dashboard and report construction.
• Background in predictive models and the implementation of machine learning in production settings.
• Certifications such as Databricks Data Engineer Associate and/or Azure DP-203 will be considered a plus.
• Experience in the insurance sector or within high-volume financial platforms.
• Proficiency in English.

Personal Qualities

• A candidate is expected to embrace challenges, meaning when an issue arises (such as a pipeline breaking in production), they will actively seek the root cause and resolve the problem.
• Effective communication skills are essential; being able to convey complex information without unnecessary jargon is crucial to ensure business teams can work effectively with the data provided.
• Commitment to quality is non-negotiable; launching a pipeline without testing or documenting afterward would not align with the company’s standards. You will be expected to manage projects independently from conception to implementation without constant supervision.

Working Environment

Trinca adopts a contract model allowing for autonomy and remote work flexibility. The culture fosters a work environment where individuals are encouraged to build the foundation of the data structure for a real-scale insurance platform.

Conclusion

Joining Trinca as a Senior Data Engineer means becoming a part of a forward-thinking team that values technology as a means to achieve real impact, not an end goal. If you desire to work in a place where genuine human connections are prioritized, technology is a tool for purpose, and every contribution matters, this may be the right place for you, helping to shape the future with your expertise in data.

Apply today and be part of a company that builds what’s next!

This job offer was originally published on weworkremotely.com