Data Systems Engineer
2 semanas atrás
We are on a mission to humanize the digital transformation of healthcare at Knok. Through our Digital Front Door strategy, we connect patients, providers, and healthcare professionals in one place.
Our API-first white-label platform enables a continuous, engaging, and personalised healthcare experience for all conditions through a cutting-edge Patient Journey Engine.
We leverage ready-to-use data to improve care automation and increase financial savings. Since 2015, we have enabled more than 2.5 million clinical interactions in over 12 countries.
Our platform is scalable and AI-ready, enhancing the power of data-driven care to deliver better outcomes during all stages of life.
About the Role
We are seeking a Junior Data Engineer to assist in building and maintaining data systems while constructing datasets that meet the company's analytical requirements.
As a Junior Data Engineer, you will play a crucial role in implementing methods to enhance data reliability and quality, as well as converting raw data from various sources into consistent and machine-readable formats.
Key Responsibilities
- Assist in combining raw information from different sources.
- Support in analyzing and organizing raw data.
- Assist in building and maintaining data systems and ETL pipelines.
- Help monitor and test the pipelines for reliability.
- Aid in evaluating business needs and objectives.
- Assist in interpreting trends and patterns within the data.
- Contribute to complex data analysis and report findings.
- Explore opportunities to enhance data quality and reliability.
- Contribute to the development of analytical tools and programs.
- Collaborate with data analysts, product managers, and other stakeholders on various projects.
- Assist in monitoring the cost of data systems.
About You
To be considered for this role, here are the skills we're looking for:
- Basic knowledge of Python language (Object-Oriented Programming, unit testing, APIs, etc).
- Familiarity with ETL pipelines.
- Familiarity with SQL.
- Exposure to Airflow is a plus.
- Exposure to Version Control systems (e.g., GitHub, Gitlab).
- Exposure to columnar databases (e.g., Redshift, BigQuery, Snowflake).
- Understanding of dimensional modeling (e.g. Star Schema)
- Analytical skills.
- Degree in Computer Science, IT, or a related field; a Master's degree is a plus.
- Exposure to GCP is a plus.
- Exposure to Heroku is a plus.
- Exposure to dbt is a plus.
- Ability to communicate technical concepts to non-technical stakeholders effectively.
- Problem-solving skills to address data-related challenges efficiently.
- Analytical mindset for evaluating data solutions and making informed decisions.
- Collaborative approach to work effectively within a multidisciplinary team.
- Excellent time management and task prioritization skills.
- Willingness to learn and stay updated with evolving data technologies.
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