Data Engineer

About Us:

Hytech is a leading fintech company specializing in cutting-edge financial technology solutions. Our innovative platforms and applications empower our clients to manage their finances efficiently, securely, and with unparalleled convenience. As a market leader in the fintech industry, we are dedicated to driving digital transformation and shaping the future of financial technology.

Our passion for connecting the dots extends beyond the technological realm. We foster a culture of inclusivity that values collaboration and knowledge-sharing among our team members, clients, and partners. Together, we harness the power of connection to inspire innovation, drive growth, and shape a better future for the fintech industry.

Join us at Hytech as we continue our journey of connecting the dots and paving the way to success for our clients and partners. Let us embark on a collaborative adventure, where we explore new possibilities, drive innovation, and navigate the exciting landscape of the digital world together.

Overview of Responsibilities:

The Data Engineer will oversee the company's data ingestion / integration work, including developing a data model, maintaining a data warehouse and analytics environment, and writing scripts for data ingestion / integration and analysis. This role will work closely and collaboratively with members of the Data & Analytics and Development teams to define requirements, mine and analyze data, integrate data from a variety of sources, and deploy high quality data pipelines in support of the analytics needs. He will also be responsible for creating automated reporting / data visualization system based on the request of internal stakeholders.

Description of Duties:

Maintain and build on our data warehouse and analytics environment, the home for various source data generated in the company.

Design, implement, test, deploy, and maintain stable, secure, and scalable data engineering solutions and pipelines in support of data and analytics projects, including integrating new sources of data into our central data warehouse, and moving data out to applications.

Build reports and data visualizations, using data from the data warehouse and other sources.

Produce scalable, replicable code and engineering solutions that help automate repetitive data management tasks.

Perform one-off data manipulation and analysis on a wide variety of source data.

Implement and monitor best in class security measures in our data warehouse and analytics environment.

Help other data team staff troubleshoot their SQL, Python, or R code.

Train other data team staff on these skills.

Other duties as assigned.

Qualifications:

Strong command of relational databases and SQL. Extract, Transform, and Load (ETL) data into a relational database.

Proficiency with Python or R, especially for data manipulation and analysis, and ability to build, maintain and deploy sequences of automated processes with these tools.

BA or BS in related field or equivalent work experience.

General data manipulation skills: read in data, process and clean it, transform and recode it, merge different data sets together, reformat data between wide and long, etc.

Demonstrated ability to learn new techniques and troubleshoot code without support, ex. find answers to common programming challenges on Google. In other words, be able to learn on the job.

Demonstrated ability to write clear code that is well-documented and stored in a version control system (we use Gitlab).

Demonstrated ability to work independently and be a self-starter.

Excellent listening, interpersonal, communication and problem-solving skills.

Demonstrated ability to work effectively in teams, in both a lead and support role.

Use APIs to push and pull data from various data systems and platforms.

Experience working with cloud infrastructure services like Amazon Web Services is preferred.

Effective time management skills, including demonstrated ability to manage and prioritize multiple tasks and projects.

Experience with data visualization (PowerBI, Tableau) is helpful, but not required.

Experience with Data Science is preferred, but not required.