Data Engineer

Position

Data Engineer

Atlanta, GA (Hybrid 3x in office)

Contract-to-hire

6 months-1 year

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.

• Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to ELT principles and business goals.
• Solves complex data problems to deliver 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.

• 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.