What are the responsibilities and job description for the Data Engineer position at Data Society?
About Data Society Group
At Data Society Group, we provide the highest quality, leading-edge, industry-tailored data and AI training and solutions for Fortune 1,000 companies and federal, state, and local governmental organizations. We partner with our clients to educate, equip, and empower their workforces with the skills they need to achieve their goals and expand their impact. Our portfolio of brands and services sits at the intersection of people, data, and AI and consists of:
- CDO Magazine, the trusted voice of global data and AI leadership
- The Data Lodge, a pioneer in data literacy and cultural transformation
- Data Society, delivering applied AI education and custom-built solutions
- InspiredMinds!, a convening force behind the world’s most inclusive AI community
We are working to empower the workforces of the future; if you’re as passionate about transforming workplaces with the power of Data & AI as we are, we’d love to hear from you!
About the Role
The Data Engineer is responsible for building scalable, performant data pipelines that power critical operational and analytical applications. The engineer must be able to work closely with our data science teams to build the supporting data scaffolding to orchestrate, test, and monitor data systems. This is a customer-facing role within a cross-functional team so the ability to manage timelines, work both autonomously and collaboratively, and communicate effectively are a must.
As this position will help to support federal contracts with security requirements, you must be a US Citizen to qualify. Occasional travel to client offices in Richmond, VA will be required, and preference will be given to local DMV area candidates.
This is a full-time, remote/work from home, benefits eligible position.
Responsibilities:
- Ability to build a full data pipeline from data ingestion to processing/transformation to load to visualization and analysis.
- Design and manage large-scale data warehouses, lakehouses, and/or data marts
- Build and optimize data transformation pipelines using tools like dbt to support data flow from ingestion through analytics
- Champion data governance principles and quality standards, ensuring data lineage, documentation, and metadata are maintained
- Create efficient, performant SQL-based data queries and Python-based data processing jobs
- Demonstrate ability to balance computational load, performance, and cost
Skills you bring:
- Advanced Degree in Statistics, Applied Mathematics, Data Science, Computer Science, Operations Research or other closely related other quantitative or mathematical disciplines.
- 5 years of data and analytics engineering in cloud environments
- Expertise in SQL, Python, and schema design with experience in data cataloging and governance tools
- Experienced with data transformation and ETL best practices
- Experienced with data orchestration tools like Airflow, transformation frameworks like dbt, and cloud deployment tools like Terraform.
- Demonstrated exceptional oral and written communication skills.
- The ability to work independently and in a team environment.
- The ability to work effectively across functions, levels and disciplines.
- Strong problem solving and critical thinking skills.
- Superior team-working skills, and a desire to learn, contribute, and explore.
- Experience with Snowflake, Databricks, Kafka, Flume, Spark, or Flink is a plus
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.