Position: Data Engineer
Company: CHI Software
Category: Data Science
Experience required: 3y
English level: intermediate

**Qualifications and Skills**

● Bachelor’s Degree in Computer Science or closely related discipline.
● 3+ years, demonstrable, hands-on professional software development skills using Java
and/or Python.
● Demonstrable professional experience designing, building, and maintaining data
systems and processes using cloud-based platforms such as GCP, AWS, including
working knowledge in Unix/Linux OS, shell scripting, and tools.
● Developing ELT pipelines in and out of data warehouse using a combination of Java,
Python, and Snowflakes SnowSQL.
● Expertise in using AWS cloud-based systems and services to acquire and deliver data:
Fargate, Amazon API Gateway, EC2, S3, Kinesis, Glue, SNS, SQS, Lambda Function,
CloudWatch, Airflow, Step Functions, DBT, RDS, DMS, DynamoDB.
● Extensive hands-on experience working with data using SQL language.
● Experienced in CI/CD practices including unit testing, automation testing, data migration,
code quality, performance, and integration/systems testing.
● Excellent verbal and written communications skills with the ability to clearly present
ideas, concepts, and solutions.
● Demonstrated willingness and ability to effectively work with various team members
when gathering requirements, delivering solutions, and eliciting suggestions and
feedback.
● Extremely quick learner both in terms of new technical skills and acquiring domain
knowledge.

**Job Function**

● Liaise with key stakeholders to understand requirements, business definitions, and the
potential value of different data.
● Understanding data transformation and translation requirements and which tools to
leverage to get the job done.
● Design and build well-engineered data systems and services to support big data
analytics using AWS cloud services and Snowflake DWH.
● Assure accuracy of data processing and outputs through consistently high software
development skills, adherence to best practice, thorough testing, and peer reviews.
● Understanding data pipelines and modern ways of automating ELT data pipelines using
orchestration tools.
● Design and implement API with a highly available, cloud-first mentality that leverages
reusable components and microservice architectures.
● A solid experience and understanding of architecting, designing, and operationalization
of large-scale data and analytics solutions on Cloud Data Warehouse such as Google
BigQuery or Snowflake is a must.
● Habitually approach problem solving with creativity and resourcefulness; carefully
evaluate risks and determine correct courses of action when completing tasks.
● Provide production support for Data Warehouse issues such as data load problems,
transformation translation discrepancies.


**Job Summary**

As a data engineer, you will be responsible for designing and implementing new AWS-based
data solutions – new data processing, datasets, and systems to support various advanced
analytics needs. This involves working with the existing engineering team, data scientists,
analysts and the business to understand requirements and data needs and definitions, all the
while thinking creatively about what data can be best exploited to solve a wide array of business
problems. You will create data flows to integrate with multiple external sources including APIs,
database connections, and flat files. You will liaise with members of the wider Data & Analytics
teams to ensure alignment with existing systems and consistency with internal standards and
best practices.