Data Engineer

SoHo Dragon•Atlanta, GA

54d•Hybrid

About The Position

The data engineer is responsible for designing, building, and maintaining the systems and infrastructure needed for data storage, processing, and analysis. The data engineer will work with a multidisciplinary Agile team to build high-quality data pipelines, generate insights from connected data, and advance the company's data-driven decision-making capabilities.

Requirements

Experience in building data pipelines and deploying/maintaining them following modern DE best practices -target tech stack: Python OSS Data Ecosystem (PySpark, pandas, Dash); knowledge of SQL, DBT is a plus
Heavy experience with Azure Data Factory is a must.
Experience with designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks, or distributed databases, like Redshift and Snowflake, and experience with housing,accessing, and transforming data in a variety of relational databases
Strong understanding of agile methodologies and experience as a Data Engineer on a cross-functional agile team preferred
Software Engineering fundamentals and software development tooling (e.g., Git, CI/CD, JIRA) and familiarity with the Linux operating system and the Bash/Z shell
Experience with cloud database technologies (e.g., Azure) and developing solutions on cloud computing services and infrastructure in the data and analytics space
Basic familiarity with BI tools (e.g., Alteryx, Tableau, Power BI, Looker)
Experience working in data engineering or data architect role
Bachelor’s degree in computer science, statistics, engineering, or a related field
3+ years of experience as a Data Engineer, preferably in a large organization
Focused on agile delivery with a “fail-fast, succeed early” mindset and measurable outcomes
Flexibility to changes in work direction as the project develops according to highest-priority business needs
Strong work ethic; ability to work at an abstract level and gain consensus
Exemplary organizational skills with attention to detail, access, and quality assurance
Excellent communication and listening skills, collaborating closely with multidisciplinary team members
Have a “can do” attitude and thrive on a “test and learn” mentality

Responsibilities

Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to ELT principles and business goals.
Solves complex data problems to delivers insights that helps business achieve its goals.
Creates data products for engineer, analyst, and data scientist team members to accelerate their productivity.
Engineer effective features for modelling in close collaboration with data scientists and businesses.
Leads the evaluation, implementation and deployment of emerging tools and process for analytics data engineering in order to improve productivity as a team and quality.
Partners with machine learning engineers, BI, and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
Fosters a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.
Advises, consults, mentors, and coach other data and analytic professionals on data standards and practices.
Develops and delivers communication and education plans on analytic data engineering capabilities, standards, and processes.
Learns about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics as necessary to carry out role effectively.