Senior Data

1 day ago

Stockholm, Sweden Rasulson Consulting AB Full time

In this pivotal role, you will shape the future of our data and AI capabilities by designing, building, and optimizing robust data pipelines, AI-driven workflows, and MLOps solutions. Your expertise will drive operational excellence and enable data-driven decision-making, while collaborating closely with cross-functional teams to ensure that our technical implementations support our broader business objectives.

Key Responsibilities

Data Engineering & Solution Development

– Design & Implementation: Develop scalable data pipelines using tools such as BigQuery, DBT, and advanced SQL optimization techniques.

– Real-Time Data Processing: Implement real-time data streaming solutions with technologies like Kafka, Pub/Sub, and scheduling tools such as Cloud Composer (Apache Airflow).

– Data Infrastructure Management: Build and maintain ETL workflows, data lakes, and data warehouses to support both analytical and AI applications.

– Infrastructure as Code (IaC): Utilize Terraform to implement secure, scalable, and automated infrastructure solutions.

– Data Governance: Ensure proper data governance, lineage, and access controls through the use of IAM policies and Data Catalog tools.

MLOps & AI-Driven Solutions

– End-to-End ML Pipelines: Develop and optimize comprehensive machine learning pipelines using platforms such as Vertex AI Pipelines, Kubeflow, and Dataflow.

– Automation: Streamline processes such as feature engineering, model deployment, and monitoring in production environments.

– Advanced AI Techniques: Work with cutting-edge AI methodologies including prompt engineering, generative AI (GenAI), Retrieval-Augmented Generation (RAGs), and agentic workflows.

– Collaborative Optimization: Partner with Data Scientists to fine-tune model performance and ensure smooth, scalable integration into production systems.

DevOps & Software Engineering

– Code Quality: Deliver high-quality software using Python—leveraging object-oriented programming, unit testing (with Pytest/Unittest), and tools like flake8, mypy, black, and SonarQube.

– CI/CD Pipelines: Design and maintain continuous integration and delivery pipelines using GitHub Actions, Azure DevOps, and Docker containerization.

– GitOps Practices: Implement GitOps methodologies to facilitate seamless collaboration, effective version control, and automated deployments.

Stakeholder Collaboration

– Business Alignment: Translate complex business needs into practical technical solutions, ensuring strategic alignment across departments.

– Team Collaboration: Work closely with teams across Data Science, AI, and other business functions to optimize data workflows and system integration.

– Knowledge Sharing: Contribute to the team’s technical expertise by leading workshops, presentations, and maintaining clear, accessible documentation.

Dashboarding & Data Visualization

– Interactive Dashboards: Create dynamic dashboards using tools like Power BI, Tableau, or Looker to deliver real-time insights.

– Data Integration: Ensure seamless connectivity between cloud-based databases (e.g., BigQuery) and BI tools for effective data visualization.

– Best Practices: Apply industry-standard techniques in data modeling and visualization to generate meaningful business insights.

Documentation & Continuous Improvement

– Comprehensive Documentation: Maintain clear and structured documentation for all architectural designs, data workflows, and engineering decisions.

– Quality Assurance: Regularly conduct code reviews, performance audits, and optimizations to enhance system efficiency and scalability.

– Innovation: Stay abreast of emerging trends in AI, MLOps, and cloud engineering to continuously improve our data infrastructure and processes.

Qualifications & Experience

– Educational Background: A bachelor’s or master’s degree in Computer Science, Data Science, or a related field.

– Professional Experience: At least 5 years of experience in data engineering, cloud architecture, and developing machine learning pipelines.

– Technical Expertise: Proven proficiency with Google Cloud Platform (GCP) technologies, including BigQuery, Pub/Sub, Dataflow, Cloud Composer, Vertex AI Pipelines, and Kubeflow.

– Programming & DevOps Skills: Strong command of Python and SQL, with hands-on experience in DevOps tools, Terraform, Unix-based systems, and shell scripting.

– Advanced AI & MLOps: Experience with feature engineering, model deployment, AI prompt engineering, generative AI, and Retrieval-Augmented Generation (RAGs).

– Visualization & Modeling: Skilled in developing dashboards and performing data modeling using tools like Power BI, Tableau, or Looker.

Personal Attributes

– Data-Driven Mindset: You approach challenges with a focus on data and customer-centric solutions.

– Proactive & Adaptable: You thrive in dynamic environments and are committed to continuous learning and improvement.

– Collaborative Spirit: You excel in teamwork and cross-departmental collaboration, ensuring cohesive and integrated solutions.

If you’re ready to drive innovation and transform how data and AI propel business success, we invite you to bring your expertise and passion to our team. Your work will be instrumental in developing scalable, efficient solutions that support our digital transformation and growth initiatives.

About Rasulson Consulting

Rasulson Consulting is a specialized staffing and recruitment firm focused on the IT sector. We collaborate with leading tech companies and innovative startups to provide exciting career opportunities for individuals passionate about digital development. With our deep technical expertise and extensive network, we efficiently match the right talents with the right assignments. At Rasulson Consulting, you’ll receive personalized guidance, regular feedback, and the chance to take the next step in your IT career.

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