SoHo Dragon
Position: Data Engineer
Location: Atlanta, GA (Hybrid 3x in office)
Employment Type: Contract-to-hire
Contract Duration: 6 months – 1 year
Overview 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.
Responsibilities
Design, develop, optimize, and maintain data architecture and pipelines that adhere to ELT principles and business goals.
Solve complex data problems to deliver insights that help the business achieve its goals.
Create data products for engineers, analysts, and data scientists to accelerate their productivity.
Engineer effective features for modelling in close collaboration with data scientists and business stakeholders.
Lead the evaluation, implementation, and deployment of emerging tools and processes for analytics data engineering to improve team productivity and quality.
Partner with machine learning engineers, BI professionals, and solutions architects to develop technical architectures for strategic enterprise projects.
Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.
Advise, consult, mentor, and coach other data and analytic professionals on data standards and practices.
Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes.
Continuously learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics as necessary to carry out the role effectively.
Key Skills
Experience 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 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 development tooling (e.g., Git, CI/CD, JIRA) and familiarity with the Linux operating system and 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 a data engineering or data architect role.
Qualifications & Technical Skills
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.
Interpersonal Mindset & Behaviors
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.
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Location: Atlanta, GA (Hybrid 3x in office)
Employment Type: Contract-to-hire
Contract Duration: 6 months – 1 year
Overview 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.
Responsibilities
Design, develop, optimize, and maintain data architecture and pipelines that adhere to ELT principles and business goals.
Solve complex data problems to deliver insights that help the business achieve its goals.
Create data products for engineers, analysts, and data scientists to accelerate their productivity.
Engineer effective features for modelling in close collaboration with data scientists and business stakeholders.
Lead the evaluation, implementation, and deployment of emerging tools and processes for analytics data engineering to improve team productivity and quality.
Partner with machine learning engineers, BI professionals, and solutions architects to develop technical architectures for strategic enterprise projects.
Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.
Advise, consult, mentor, and coach other data and analytic professionals on data standards and practices.
Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes.
Continuously learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics as necessary to carry out the role effectively.
Key Skills
Experience 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 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 development tooling (e.g., Git, CI/CD, JIRA) and familiarity with the Linux operating system and 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 a data engineering or data architect role.
Qualifications & Technical Skills
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.
Interpersonal Mindset & Behaviors
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.
#J-18808-Ljbffr