Astro Sirens LLC

Business Intelligence Developer

• Design and implement business intelligence (BI) solutions that translate complex data into actionable insights for various business units.
• Develop and maintain interactive dashboards and reports using BI tools like Power BI, Tableau, or similar to provide real-time business visibility.
• Collaborate with data scientists, engineers, and business stakeholders to define data requirements and deliver effective BI solutions.
• Extract, clean, and transform large datasets from various sources to enable accurate and insightful reporting.
• Analyze data using statistical techniques and machine learning models to uncover trends, patterns, and predictive insights.
• Work with cloud platforms such as AWS (e.g., Redshift, S3) and Azure (e.g., Synapse, Azure Data Lake) to manage and optimize data storage.
• Leverage Python libraries (e.g., Pandas, NumPy, scikit-learn) for data manipulation, analysis, and advanced reporting.
• Build and optimize ETL/ELT processes to move data efficiently into data warehouses or BI tools.
• Ensure data integrity by automating data validation processes and improving data quality.
• Create custom reports and automated dashboards with Excel, leveraging advanced Excel functions such as pivot tables, vLOOKUP, and Power Query for business analysis.
• Provide ad-hoc reporting and data analysis as requested by business teams to support decision-making.
• Work with containerization technologies like Docker and orchestration tools like Kubernetes to streamline deployment and scaling of data systems.
• Collaborate across teams to ensure that the BI and analytics processes meet business objectives and compliance standards.

Senior Data Analyst / BI Developer

Backend Engineer

• Design, develop, and maintain scalable, secure applications using Go/Golang, JavaScript, and modern frontend technologies.
• Build and maintain cloud-based infrastructure on AWS and Azure for scalable, high-performance systems.
• Develop and implement RESTful APIs to integrate frontend and backend systems seamlessly.
• Collaborate with product and design teams to deliver high-quality software solutions, maintaining excellent communication throughout the process.
• Utilize Docker and Kubernetes to containerize applications, streamline deployment, and ensure smooth CI/CD pipelines.
• Troubleshoot, debug, and optimize applications for performance, scalability, and reliability.
• Write efficient, maintainable, and testable code while following best practices in Go/Golang and JavaScript.
• Participate in code reviews to ensure adherence to coding standards, quality, and maintainability.
• Implement and manage CI/CD pipelines using AWS and Azure services for efficient and automated deployments.
• Ensure security and data protection across applications and services in cloud environments.
• Stay up-to-date with the latest technologies and industry trends to continuously enhance development practices and tools.

Senior Full Stack Engineer, Golang

• Design, develop, and maintain scalable and secure applications using Java for backend services, with strong emphasis on frameworks like Spring Boot, Spring Cloud, and Hibernate.
• Build and maintain cloud-based infrastructure using AWS (EC2, S3, Lambda, RDS) and Azure (Azure Functions, Azure SQL Database, App Services) to ensure high performance and scalability.
• Develop and implement RESTful APIs and GraphQL for seamless integration between frontend and backend systems.
• Work with Java-based tools and libraries such as Apache Kafka, ActiveMQ, RabbitMQ, and JMS for messaging and event-driven architecture.
• Collaborate with product and design teams to deliver high-quality, user-friendly software solutions.
• Utilize Docker and Kubernetes for containerization, ensuring smooth deployments, scalability, and easy management of microservices.
• Troubleshoot, debug, and optimize applications for performance, scalability, and reliability using tools like JProfiler, New Relic, or Prometheus.
• Write clean, efficient, maintainable, and testable code following Java best practices and patterns.
• Participate in code reviews to ensure adherence to coding standards, quality, and maintainability.
• Implement and manage CI/CD pipelines using tools like Jenkins, GitLab CI, CircleCI, and cloud services like AWS CodePipeline and Azure DevOps.
• Ensure security and data protection across applications and services, utilizing tools like OWASP ZAP, Spring Security, and JWT for secure communication.
• Stay up-to-date with the latest Java technologies, frameworks, and industry trends to continuously enhance development practices.

Senior Java Full Stack Engineer

Data Engineer

• Design, implement, and maintain robust and scalable data pipelines using AWS, Azure, and containerization technologies.
• Develop and maintain ETL/ELT processes to extract, transform, and load data from various sources into data warehouses and data lakes.
• Collaborate with data scientists, analysts, and other engineers to ensure seamless data flow and availability across the organization.
• Optimize data storage and retrieval performance by utilizing cloud services like AWS Redshift, Azure Synapse, or other relevant technologies.
• Work with containerization tools like Docker and Kubernetes to ensure smooth deployment, scalability, and management of data pipelines.
• Monitor, troubleshoot, and optimize data processing pipelines for performance, reliability, and cost-efficiency.
• Automate manual data processing tasks and improve data quality by implementing data validation and monitoring systems.
• Implement and maintain CI/CD pipelines for data workflow automation and deployment.
• Ensure compliance with data governance, security, and privacy regulations across all data systems.
• Participate in code reviews and ensure the use of best practices and documentation for data engineering solutions.
• Stay up-to-date with the latest data engineering trends, cloud services, and technologies to continuously improve system performance and capabilities.

Senior Data Engineer

Data Scientist

• Data Analysis & Modeling: Utilize advanced statistical methods and machine learning techniques to analyze large, complex datasets, uncovering insights and trends that inform business strategies.
• Predictive Analytics: Build predictive models to forecast business outcomes, optimize processes, and drive decision-making across various departments.
• Feature Engineering: Design and implement feature engineering techniques to improve the accuracy and performance of machine learning models.
• Collaboration: Work closely with cross-functional teams (business, product, engineering, etc.) to identify key business problems and translate them into data science solutions.
• Data Preparation: Clean, preprocess, and organize raw data from different sources to ensure it is suitable for analysis and modeling.
• Machine Learning Model Development: Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems.
• Evaluation & Optimization: Evaluate the performance of models using various metrics (e.g., accuracy, precision, recall, F1 score) and optimize them for real-world performance.
• Data Visualization & Reporting: Create clear, insightful visualizations and reports to communicate findings to non-technical stakeholders.
• Automation: Automate repetitive data processing and reporting tasks to increase efficiency and reduce manual effort.
• Research & Innovation: Stay up-to-date with the latest developments in data science, machine learning, and AI, and bring new ideas and techniques to the team.
• Deployment & Monitoring: Implement models into production environments and monitor their performance over time to ensure they meet business requirements.

Senior Data Scientist

• Design, build, and maintain scalable, reliable, and high-performance data pipelines
• Develop and manage ETL/ELT workflows to ingest data from multiple sources (APIs, databases, streaming systems, files)
• Architect and optimize data warehouses and data lakes for analytics and reporting use cases
• Ensure data quality, consistency, availability, and reliability across systems
• Collaborate with data scientists, analysts, software engineers, and business stakeholders to understand data requirements
• Implement data modeling best practices for analytical and operational workloads
• Optimize data pipelines for performance, cost efficiency, and scalability in cloud environments
• Build and maintain real-time and batch data processing systems
• Implement monitoring, logging, and alerting for data pipelines and infrastructure
• Enforce data governance, security, and compliance standards
• Document data architectures, pipelines, and best practices
• Mentor junior data engineers and contribute to improving data engineering standards and tooling across teams

• - Design, develop, and deploy machine learning models for real-world production use cases
• - Analyze large and complex datasets to extract insights that inform model development and optimization
• - Build end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment
• - Collaborate with data engineers, software engineers, product managers, and business stakeholders to define machine learning requirements
• - Implement model monitoring, performance tracking, and retraining strategies
• - Optimize models for scalability, performance, and reliability in cloud-based environments
• - Ensure data quality, reproducibility, and adherence to best practices in ML development
• - Translate machine learning outcomes into clear, actionable insights for technical and non-technical audiences
• - Contribute to improving ML standards, tools, and best practices across teams
• - Mentor junior data scientists and machine learning engineers

Senior Data Scientist / Machine Learning Engineer

Technical Recruiter

• Collaborate with the HR team to understand job requirements, role priorities, and ideal candidate profiles
• Source qualified software engineering and IT candidates through various channels, including:
• Local and global software engineer communities
• Professional networks and social media platforms
• Job boards and niche technical talent pools
• Review and filter resumes to ensure only requirement-matching candidates are submitted
• Submit candidate profiles and resumes to the HR team in a clear and organized format
• Coordinate and schedule initial interviews using the HR team’s Calendly link
• Post and maintain job descriptions across relevant platforms and social channels
• Ensure a smooth and professional candidate experience throughout the sourcing and coordination process
• Maintain accurate records of candidate pipelines and sourcing activity

Senior Data Analyst / BI Developer

Senior Full Stack Engineer, Golang

Senior Java Full Stack Engineer

Senior Data Engineer

Senior Data Scientist

Senior Data Engineer

Senior Data Scientist / Machine Learning Engineer

Technical Recruiter – Software Engineering Focus