Sr. Data Engineer
Sureify drives customer engagement between the customer and their insurance company by incorporating web & mobile apps into the insurance product experience. Our product is controlled by our backend dashboard, so insurers can get the latest iOT data streaming in. The SaaS platform is designed to ensure that insurers never miss opportunities to increase engagement with their existing customer base.
We are looking for a Data Engineer with strong expertise in Python and SQL to design, build, and maintain scalable data pipelines and ETL processes. In this role, you will work closely with analytics and business teams to enable seamless data access and support data-driven decision-making, while also driving AI/ML adoption within the team by building ML-ready data pipelines and contributing to the end-to-end lifecycle of machine learning use cases.
Responsibilities:
Design, build, and maintain scalable and reliable data pipelines using Python and workflow orchestration tools like Apache Airflow.
Develop and optimize ETL/ELT workflows to ingest, transform, and load data from multiple sources such as REST APIs, databases, and cloud storage (AWS S3).
Design and manage data models, handle schema migrations, and optimize complex queries across Amazon Redshift, PostgreSQL, and MySQL.
Ensure high standards of data quality, integrity, and availability to support analytics, reporting, and machine learning use cases.
Drive the adoption of AI/ML capabilities within the team, leveraging prior experience in data science projects.
Take ownership of building and evolving ML-ready data pipelines and workflows.
Contribute to the end-to-end AI/ML lifecycle, including data preparation, feature engineering, model support, and deployment enablement.
Introduce and help the team adopt modern tools and technologies in AI/ML and data engineering.
Identify opportunities to apply predictive analytics and machine learning to solve business problems.
Monitor, troubleshoot, and resolve data pipeline failures and performance bottlenecks.
Maintain clean, version-controlled code using Git, and follow best practices through peer code reviews.
Document data pipelines, workflows, and system architecture for maintainability and knowledge sharing.
Skills And Qualifications
3+ years of experience in data engineering, with exposure to AI/ML projects and full lifecycle involvement.
Strong proficiency in Python for data processing, automation, and pipeline development.
Hands-on experience with workflow orchestration tools like Apache Airflow.
Experience working with AWS services such as S3, Redshift and familiarity with ML-related services (e.g., SageMaker) is a plus.
Strong knowledge of relational databases (PostgreSQL, MySQL) with expertise in query optimization and performance tuning.
Experience with DBT for data transformation and modeling.
Solid understanding of ETL/ELT concepts, data warehousing, and data modeling techniques.
Practical experience in machine learning workflows, including data preprocessing, feature engineering, and model evaluation.
Familiarity with AI/ML lifecycle, including data preparation, training, validation, deployment, and monitoring.
Experience with tools/frameworks such as MLflow, SageMaker, or similar platforms is an advantage.
Strong interest in exploring and adopting new technologies in AI/ML and data engineering.
Ability to guide and upskill team members in ML-related concepts and best practices.
Good communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.
Benefits
Here is a glimpse of some of the benefits we offer:
Competitive Salary
Medical insurance & Accidental insurance to keep you and your family healthy.
Possibility to travel around the world for seminars and learning on the latest technologies in the industry.
Great team to work with, exposure to the best technologies in the industry.
Sureify is an equal opportunity employer and enthusiastically encourages people from a wide variety of backgrounds and experiences to apply.
