Data Engineer II Position Available In Volusia, Florida

Data Engineer II Censys Technologies Corporation 1808 Concept Court, Daytona Beach, FL 32114

About Us:

The following is what we at Censys call our DNA Derivatives. It is fundamental to the job that you align with them. Please review them before applying. Thank you and we look forward to seeing your applications! Censys Technologies DNA Derivatives 5

Areas of Excellence:

Steward resources with excellence | Obsess over customers | Create new technologies | Improve continuously | Communicate with excellence 4

Core Values:

Steadfast Customer Service | Quality | Integrity | Love 3 Fundamental Beliefs We believe enrichment comes when technology enables problem solving. We believe our natural order is to achieve our maximum potential as individuals and as an organization to make the world wiser. We believe omniscience of humanity’s assets is the cornerstone of value creation. 2 Pillars of Identity Strength•capacity to withstand great force and pressure Courage•the ability to name fear and not give it a foothold 1

Mission:

Enrich lives through asset intelligence technology.

Salary Range:

$100,000•120,000

Job Description:

Censys Technologies is seeking a skilled and motivated Data Engineer II to join our dynamic team. In this role, you will be instrumental in designing, building, maintaining, and optimizing the data infrastructure that powers our CensWise™ platform. You will work closely with our AI/ML engineers, software developers, and product managers to ensure robust, scalable, and efficient data pipelines and databases that support the entire lifecycle of our

CV/AI/ML

models, from data ingestion and processing to model training and deployment at the edge and in the cloud.

Key Responsibilities:

Data Pipeline Development & Optimization:

Design, develop, and maintain scalable and reliable data pipelines for ingesting, transforming, and loading large volumes of structured and unstructured data from diverse sources (e.g., sensor data, imagery, telemetry).

Database Management & Architecture:

Design, implement, and manage efficient and scalable database solutions (SQL and NoSQL) to store and retrieve data critical for AI/ML model training, validation, and inference.

ETL/ELT Processes:

Build and manage robust ETL/ELT processes to ensure data quality, integrity, and availability.

Cloud & Edge Data Solutions:

Develop and implement data solutions optimized for both cloud environments (e.g., AWS, Azure, GCP) and resource-constrained edge devices.

Data Quality & Governance:

Implement data quality checks, monitoring, and anomaly detection to ensure the reliability of data used for model development and deployment. Contribute to data governance best practices.

Performance Tuning:

Monitor and optimize the performance of data pipelines and database systems, identifying and resolving bottlenecks.

Collaboration:

Work collaboratively with AI/ML engineers to understand their data requirements and provide them with clean, well-structured data for model development. Infrastructure as Code (IaC): Utilize IaC principles and tools (e.g., Terraform, CloudFormation) for provisioning and managing data infrastructure.

Monitoring & Alerting:

Implement and maintain monitoring and alerting systems for data pipelines and databases to ensure high availability and proactive issue resolution.

Documentation:

Create and maintain comprehensive documentation for data architectures, pipelines, and processes.

Stay Current:

Keep abreast of new technologies and best practices in data engineering, big data, and MLOps.

Required Qualifications & Skills:

Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field. 3+ years of hands-on experience in data engineering or a similar role. Proven experience in designing, building, and maintaining data pipelines (e.g., using Apache Airflow, Kafka, Spark, Flink, or similar technologies). Strong proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL). Experience with NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB). Proficiency in at least one programming language commonly used in data engineering (e.g., Python, Scala, Java). Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services (e.g., S3, Redshift, BigQuery, Azure Blob Storage, Azure Data Factory). Understanding of data warehousing concepts and technologies. Familiarity with data modeling techniques. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Ability to work independently and as part of a team in a fast-paced environment.

Preferred Qualifications & Skills:

Master’s degree in a relevant field. Experience with MLOps principles and tools. Experience with data pipeline and workflow orchestration tools (e.g., Kubeflow Pipelines, Argo Workflows). Knowledge of containerization technologies (e.g., Docker, Kubernetes). Experience with data visualization tools (e.g., Tableau, Power BI, Grafana). Familiarity with edge computing concepts and data processing on edge devices. Experience working with geospatial data or imagery. Understanding of

CV/AI/ML

model development lifecycles. Contributions to open-source data engineering projects.

Job Type:

Full-time Pay:

$100,000.00•$120,000.00 per year

Benefits:

Health insurance Paid time off Parental leave

Schedule:

8 hour shift Day shift Monday to

Friday Work Location:

In person