About this role
Description
In this role, you'll contribute across the stack: developing ingest pipelines, building scalable REST APIs, and facilitating data exploration and understanding. The platform supports large-scale data ingestion, complex queries, and interactive analysis. While your primary focus will be on the data-pipeline layer, you’ll collaborate closely with other sub-teams to ensure end-to-end functionality and performance. We’re looking for someone excited to work across the system and to improve team processes and tooling, especially for faster integration of new data sources.
Responsibilities
- Lead the design and implementation of data-processing workflows
- Manage all aspects of the data-processing lifecycle (collection, discovery, analysis, cleaning, modeling, transformation, enrichment, validation)
- Develop and maintain data models and JSON Schemas to ensure integrity and consistency
- Collaborate with analysts and engineers to meet data requirements
- Manage and optimize data storage/retrieval in Elasticsearch and Dgraph (plus MongoDB and Redis)
- Orchestrate dataflow using Apache NiFi
- Mentor teammates on best practices for data processing and software engineering
- Use AI platforms to support hybrid automated/manual data transformation, code generation, and schema management
- Work with analysts, product owners, and engineers to ensure solutions meet operational needs
- Propose and implement process improvements for faster delivery of new data sources
Required Skills & Experience
- Strong data-wrangling and dataflow background (discovery, mining, cleaning, exploration, enrichment, validation)
- Proficiency in JSON and JSON Schemas (or similar)
- Solid data-modeling experience
- Experience with NoSQL databases (Elasticsearch, MongoDB, Redis, graph DBs)
- Familiarity with dataflow tools such as Apache NiFi
- Extensive experience in Python or Java (both preferred)
- Experience using generative AI for code and data transformation
- Git for version control; Maven for build automation
- Comfortable in a Linux development environment
- Familiarity with Atlassian tools (Jira, Confluence)
- Strong communication and teamwork skills
Nice to Have
- Experience with various corporate data formats
- Knowledge of Kafka or RabbitMQ
- Proficiency in Java/Spring (Boot, MVC/REST, Security, Data)
- AWS (EC2, S3, Lambda) experience
- API design for data services
- Frontend experience (modern JS + Vue.js or similar)
- CI/CD (e.g., Jenkins), automated testing (JUnit)
- Docker, Kubernetes, and other containerization tech
- DevOps tools (Packer, Terraform, Ansible)
Qualifications
- 12+ years of relevant experience and a B.S. in a technical discipline
- (Four additional years of experience may substitute for a degree)
In this role, you'll contribute across the stack: developing ingest pipelines, building scalable REST APIs, and facilitating data exploration and understanding. The platform supports large-scale data ingestion, complex queries, and interactive analysis. While your primary focus will be on the data-pipeline layer, you’ll collaborate closely with other sub-teams to ensure end-to-end functionality and performance. We’re looking for someone excited to work across the system and to improve team processes and tooling, especially for faster integration of new data sources.
Responsibilities
- Lead the design and implementation of data-processing workflows
- Manage all aspects of the data-processing lifecycle (collection, discovery, analysis, cleaning, modeling, transformation, enrichment, validation)
- Develop and maintain data models and JSON Schemas to ensure integrity and consistency
- Collaborate with analysts and engineers to meet data requirements
- Manage and optimize data storage/retrieval in Elasticsearch and Dgraph (plus MongoDB and Redis)
- Orchestrate dataflow using Apache NiFi
- Mentor teammates on best practices for data processing and software engineering
- Use AI platforms to support hybrid automated/manual data transformation, code generation, and schema management
- Work with analysts, product owners, and engineers to ensure solutions meet operational needs
- Propose and implement process improvements for faster delivery of new data sources
Required Skills & Experience
- Strong data-wrangling and dataflow background (discovery, mining, cleaning, exploration, enrichment, validation)
- Proficiency in JSON and JSON Schemas (or similar)
- Solid data-modeling experience
- Experience with NoSQL databases (Elasticsearch, MongoDB, Redis, graph DBs)
- Familiarity with dataflow tools such as Apache NiFi
- Extensive experience in Python or Java (both preferred)
- Experience using generative AI for code and data transformation
- Git for version control; Maven for build automation
- Comfortable in a Linux development environment
- Familiarity with Atlassian tools (Jira, Confluence)
- Strong communication and teamwork skills
Nice to Have
- Experience with various corporate data formats
- Knowledge of Kafka or RabbitMQ
- Proficiency in Java/Spring (Boot, MVC/REST, Security, Data)
- AWS (EC2, S3, Lambda) experience
- API design for data services
- Frontend experience (modern JS + Vue.js or similar)
- CI/CD (e.g., Jenkins), automated testing (JUnit)
- Docker, Kubernetes, and other containerization tech
- DevOps tools (Packer, Terraform, Ansible)
Qualifications
- 12+ years of relevant experience and a B.S. in a technical discipline
- (Four additional years of experience may substitute for a degree)
Tech stack
MongoDBRedisPythonJavaKafkaAWS
About Neural Solutions
Neural Solutions is hiring for the full-stack software engineer role. NewJob aggregates active openings directly from Neural Solutions's applicant tracking system, so this listing is current.
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