Job: Data Engineer

Phyton, SQL, Spark

Remote

Full Time

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About Our client

Headquartered in the heart of Miami’s tech community, Our client is pioneering Direct-to-Consumer eCommerce for perishable products. Our client’s smart logistics engine increases customer lifetime value and retention with higher quality deliveries, and predictable shipping. We are a rapidly growing team that is backed by some of the best industry investors and advisors.

They are a young and dynamic company with a passion for revolutionizing the industry. Their team is comprised of innovative and driven individuals who are committed to pushing boundaries and delivering exceptional results. They are excited about the future and are looking for talented individuals who share their vision and are ready to join them on this exciting journey.

About the Role

Our client is seeking a detail-oriented Data Engineer to join their team. As a Data Engineer, you will be responsible for designing, developing, and maintaining their data infrastructure, modeling large amounts of data, and optimizing their data systems and pipelines for efficiency and reliability. You will work with the team to help drive analysis and insights to support both pre-sales and post-sales efforts. The ideal candidate will have a strong technical background, as well as good business acumen and an eagerness to learn.

Key Responsibilities:

Design, build, and maintain data processing systems, governance, and infrastructure
Develop and optimize data pipelines to ensure data accuracy, efficiency, and reliability with internal and 3rd party APIs
Build end-to-end ETL processes and data flow architectures
Work closely with key business stakeholders and customers to understand their data needs and provide solutions
Develop and maintain analytics data models
Develop and maintain dashboard and reporting solutions
Assist in the implementation of Unity Catalog
Collaborate with cross-functional teams to drive data-driven decision making
Monitor and troubleshoot data processing issues and help ensure trustworthiness and accuracy across systems
Help in developing data quality standards and ensure adherence to those standards
Stay up-to-date with emerging trends and technologies in data processing and analytics engineering

Skills and Qualifications:

Proficiency in Python & SQL; preferred experience with Spark
Experience with cloud computing platforms; preferred Azure or AWS
Experience with data processing tools; preferred Databricks
Experience with data modeling and database design, star/snowflake schemas, etc.
Familiarity with data visualization tools such as Power BI or Tableau
Familiarity with data lakes on cloud platforms such as Azure Data Lake Storage or AWS Lake Formation
Understanding of data analytics and machine learning concepts and techniques, and where/how to apply them
Strong problem-solving skills and attention to detail
Excellent communication and collaboration skills
Team player with willingness to learn and grow as the company grows