Position: Data Engineer
Company: Svitla Systems
Experience required: 5y
English level: upper

Svitla Systems Inc. is looking for a Data Engineer for a full-time position (40 hours per week) in Ukraine. Our client is a practice management software for therapists, counselors, and every type of health and wellness professional. The core product provides the necessary features to run the practice, like calendar syncs, billing, SOAP notes, and forms to help meet the legal and ethical requirements to document treatment and protect patient information. The all-in-one practice management solution for private practices to serve over 169,000+ practitioners in the health & wellness space. The leading EHR in the field. It provides business management with features like AutoPay, online booking, telehealth, and customizable documentation and notes. We are seeking a Data Engineer to take the company’s data engineering to the next level of the data-driven/data-focused journey. The Data and Analytics Team is responsible for the data across the enterprise, organized into three functions. Information delivery is provided by the data & analytics group, and the analytics itself is enabled by data engineering and Infrastructure groups. Data Engineering and Architecture covers data ingestion and transformations across the analytics platform, enterprise data architecture, and the product’s database backend architecture and data access layer. This role will be leasing the data ingestion efforts within the Data Engineering & Architecture Team. This enables data to be sanctified, making it usable for decision-making. Data governance includes data stewardship, lineage, quality, and security. They employ best practices in delivering each of these functions to the utmost benefit of the organization. As the data vision gets implemented and the company grows, there are many opportunities for personal growth.

**Requirements:**
- 8+ years of progressive professional experience is preferred.
- Proficiency in SQL, statistical/window functions, and complex data types.
- Expertise in relational technology, data modeling, and in dimensional modeling. 
- Expertise in at least two database engines, preferably MySQL, Snowflake, or Athena. 
- Background in metadata-driven and database-centric concepts.
- Understanding of database performance and data transformations.
- Understanding ETL and ETL tools, including Airflow/Prefect, and DBT. 
- Knowledge of ELT and schema-on-read concepts.

**Responsibilities:**
- Partner with analysts to build scalable systems that help unlock the value of data from a wide range of sources such as backend databases, event streams, and marketing platforms:
- Consult with the Product and Engineering Teams in the creation of new data in the production environment;
- Create company-wide alignment through standardized metrics across the company;
- Promote the importance of dimensional data models in communicating across the organization.
- Manage the complete data stack from ingestion through data consumption:
- Connect the teams and their workflows to centralized and secure databases;
- Build tools to increase transparency in reporting company-wide business outcomes;
- Define and promote data engineering best practices;
- Design scalable data solutions leveraging cloud data technologies, preferably in AWS; 
- Help define data quality and security framework to measure and monitor data quality across the enterprise.
- Excellent problem-solving & critical-thinking skills to meet complex data challenges and requirements in a fast paced, rapidly changing environment.

**Will be a plus:**
- Knowledge of big data tools and engines, Glue, DMS, and Redshift.
- Familiarity with enterprise and enterprise data architecture (data modeling and enterprise dimensional modeling).
- Skills in project & change management especially experience working in an Agile (SCRUM, Kanban) environment/team focusing on sprint-by-sprint deliveries.
- Knowledge of data ingestion tools, such as Kafka, Singer.
- Experience with at least one programming language, preferably Python. 
- Background in Unix/Linux scripting, such as Bash.
- Experience with APIs, such as via Curl.
- Experience in achieving performance through parallelism. 
- Knowledge of DAGs. 
- Experience with cloud-based infrastructure, particularly AWS 
- Knowledge of cloud storage, S3.
- Experience with data storage formats, such as Parquet, ORC.
- Experience with external tables. 
- Understanding of unstructured and semi-structured data types, JSON 
Background in Data Analytics. 
- Experience with at least one visualization tool, preferably Looker, Tableau, or Periscope. 
- Superb communication skills. 
- BS/MS degree in Engineering, Mathematics, Physics, Computer Science or equivalent experience.