Sr AWS Data Engineer

We are seeking a dynamic, innovative, and experienced Senior Data Engineer to join our fast-paced Engineering team. The ideal candidate will be responsible for designing, developing, and maintaining our data architecture, data management systems, and data processing pipelines. This position will work closely with data scientists, business stakeholders, and IT teams to meet the company's data needs and help us make data-driven decisions. The successful candidate will have a strong understanding of data lake technology and a proven track record in data engineering.

This is on-site in downtown Charlotte!

Great culture!

Job Details:

Responsibilities:

1. Design, construct, install, test, and maintain highly scalable data management systems.
2. Ensure systems meet business requirements and industry practices.
3. Integrate new data management technologies and software engineering tools into existing structures.
4. Create custom software components and analytics applications.
5. Research opportunities for data acquisition and new uses for existing data.
6. Develop data set processes for data modeling, mining, and production.
7. Collaborate with data scientists, architects, and IT team members on project goals.
8. Implement strategies that optimize statistical efficiency and data quality.
9. Interpret and analyze data problems.
10. Visualize data and create reports.
11. Experiment with new models and techniques.
12. Align data projects with organizational goals.

Qualifications:

1. BS degree in Computer Science, Engineering, or relevant field.
2. A minimum of 5 years' experience in a similar role as a Data Engineer or related specialty (e.g., Software Engineer, Business Intelligence Engineer, Data Scientist) with a track record of manipulating, processing, and extracting value from large datasets.
3. Experience working with data lake technologies.
4. Knowledge of software engineering and system design.
5. Proficient in scripting languages like Python, Java, or similar.
6. Experience with big data tools: Hadoop, Spark, Kafka, etc.
7. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
8. Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
9. Experience with AWS cloud services: EC2, EMR, RDS, Redshift.
10. Experience with stream-processing systems: Storm, Spark-Streaming, etc.
11. Demonstrated ability to build processes that support data transformation, data structures, metadata, dependency, and workload management.
12. Strong organizational and project management skills.
13. Excellent analytical and problem-solving abilities.
14. Ability to work independently and with team members from different backgrounds.
15. Excellent communication and collaboration skills.