Data Science Engineer

Key Skills

3D data processing, Apache Hadoop, Apache Kafka, Big Data Technology, Continuous Integration & Continuous Delivery - CI/CD, Data pipelines, Docker, Effective communication skills, HDFS, Kubernetes-K8s, Python Programming, R Programming, SPARK Programming, SQL

Job Description

We are seeking a highly skilled and motivated Data Science Engineer to join our team. The ideal candidate will be proficient in both data engineering and data science, capable of designing and maintaining robust data pipelines while also developing and deploying machine learning models. This role requires a blend of software engineering skills and advanced analytical abilities.

Key Responsibilities:

Data Engineering:

• Design, implement, and manage scalable data pipelines using tools such as Apache Spark, Kafka, Flink, and Airflow
• Develop ETL processes to ingest and transform data from various sources into clean, usable formats
• Ensure data quality, consistency, and reliability through monitoring and automated testing.
• Optimize database performance and storage solutions for large datasets

Data Science:

• Apply statistical analysis and machine learning techniques to build predictive models and derive insights from data
• Experiment with and evaluate different algorithms and techniques to improve model performance.
• Communicate findings through data visualizations and reports to stakeholders
• Deploy machine learning models into production and monitor their performance

Collaboration and Communication:

• Work closely with cross-functional teams, including software engineers, data analysts, and business stakeholders, to understand project requirements and deliver data-driven solutions
• Collaborate on the design and implementation of data-driven applications and services

Tooling and Automation:

• Develop and maintain scripts and tools for data processing and analysis using languages such as Python, SQL, and R
• Implement CI/CD pipelines for automated testing and deployment of data science models

Research and Innovation:

• Stay current with advancements in data engineering and data science technologies and methodologies
• Continuously improve processes and methodologies to enhance data infrastructure and analytics capabilities

Skills, Experience and Requirements

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field
• Proven experience in both data engineering and data science roles
• Proficiency in programming languages such as Python, SQL, and R
• Experience with the AWS cloud platform
• Experience with data processing frameworks (e.g., Apache Spark, Kafka) and ETL tools
• Strong understanding of machine learning algorithms and statistical techniques
• Experience with data visualization tools (e.g., Superset, Tableau, Power BI)
• Proficiency with the ELK stack
• Excellent problem-solving and troubleshooting skills
• Strong communication and collaboration skills

Preferred Qualifications:

• Experience with all cloud platforms (e.g., AWS, GCP, Azure)
• Knowledge of big data technologies (e.g., Hadoop, HDFS)
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes)
• Advanced degree (Master’s or Ph.D.) in a relevant field.

Salary Ranges

Compensation: $72,400.00/Year - $103,400.00/Year

Benefits

We offer versatile health perks, including flexible spending accounts, HSA, a 401(k) Plan with company match, ESPP, career opportunities, and a flexible time away plan; all benefits can be viewed here: DISH Benefits.

The base pay range shown is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level, and competencies; compensation is based on the role's location and is subject to change based on work location. Candidates need to successfully complete a pre-employment screen, which may include a drug test and DMV check.