Role Description As a Senior Palantir Engineer (Senior Associate) at Kainos, you will be responsible for designing and developing data processing and data persistence software components for solutions which handle data at scale. Working in agile teams, Senior Data Engineers provide strong development leadership and take responsibility for significant technical components of data systems. You will work within a multi-skilled agile team to design and develop large scale data processing software to meet user needs in demanding production environments. Your responsibilities will include: - Working to develop data processing software primarily for deployment in Big Data technologies. The role encompasses the full software lifecycle including design, code, test and defect resolution. - Working with Architects and Lead Engineers to ensure the software supports non-functional needs. - Collaborating with colleagues to resolve implementation challenges and ensure code quality and maintainability remains high. Leads by example in code quality. - Working with operations teams to ensure operational readiness. - Advising customers and managers on the estimated effort and technical implications of user stories and user journeys. - Coaching and mentoring team members. Qualifications - Strong software development experience in one of Java, Scala, or Python. - Software development experience with data-processing platforms from vendors such as AWS, Azure, GCP, Databricks. - Experience of developing substantial components for large-scale data processing solutions and deploying into a production environment. - Proficient in SQL and SQL extensions for analytical queries. - Solid understanding of ETL/ELT data processing pipelines and design patterns. - Aware of key features and pitfalls of distributed data processing frameworks, data stores and data serialization formats. - Able to write quality, testable code and has experience of automated testing. - Experience with Continuous Integration and Continuous Deployment techniques. Requirements - Experience of performance tuning. - Experience of data visualization and complex data transformations. - Experience with streaming and event-processing architectures including technologies such as Kafka and change-data-capture (CDC) products. - Expertise in continuous improvement and sharing input on data best practice. Company Description At Kainos, we believe in the power of diversity, equity and inclusion. We are committed to building a team that is as diverse as the world we live in, where everyone is valued, respected, and given an equal chance to thrive. We actively seek out talented people from all backgrounds, regardless of age, race, ethnicity, gender, sexual orientation, religion, disability, or any other characteristic that makes them who they are. We also believe every candidate deserves a level playing field. Our friendly talent acquisition team is here to support you every step of the way, so if you require any accommodations or adjustments, we encourage you to reach out. We understand that everyone's journey is different, and by having a private conversation we can ensure that our recruitment process is tailored to your needs.

• Collaborate with incident response teams to identify and implement automation opportunities. • Develop and deploy SOAR automations for detection and response. • Serve as a subject matter expert in security automation and data analytics. • Produce system analytics and document changes per Change Management best practices. • Recommend, develop, and release new use cases to optimize SOAR capabilities. • Mentor junior team members and perform quality assurance on automation work. • Participate in special projects and contribute to continuous improvement initiatives.

• Build and operate reliable, scalable data pipelines and curated datasets on the Databricks Lakehouse Platform • Collaborate with architects, analysts, and platform teams to implement batch and streaming ingestion • Develop dimensional and/or domain data models • Uplift governance and observability across the data lifecycle • Design, build, and optimising ETL/ELT pipelines using Databricks (Spark/SQL), Delta Lake, and Databricks Workflows/Jobs • Develop and maintain transformation models with dbt (Databricks adapter), including testing, documentation, and deployment via CI/CD • Implement medallion architecture patterns (bronze/silver/gold) and best-practice data modelling to support analytics and self-service consumption • Build data quality checks and observability (e.g., dbt tests, expectations, monitoring/alerting) and support lineage and documentation • Apply security and governance using Unity Catalog (access controls, table ownership, auditability) and partner with stakeholders on compliant data access • Performance tuning and cost optimisation (cluster policies, job orchestration, Spark optimisation, partitioning, Delta optimisation) and support incident/problem resolution

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Biomechanics Engineer is an intermediate-level role focused on biomechanics algorithm development and applied analysis across multiple sports markets. Working closely with the Head of Biomechanics, you will deliver consistent, high-quality results that provide actionable insights for player development, health monitoring, and scouting. This role requires a unique blend of technical expertise, specifically in managing large datasets and advanced modeling and the applied ability to interpret that data for "front office" stakeholders, coaches, and athletes. You will also assist with R&D initiatives to establish Return on Investment (ROI) and develop new use cases for biomechanics data in emerging sports. Key Responsibilities - Continue the development of biomechanics algorithms for KinaTrax Dugout and future visualization products. - Technical organization and management of large datasets for comprehensive biomechanics analyses. - Translate complex biomechanical data into actionable insights for decision-makers (coaches, front offices, medical staff) regarding athlete performance and health. - Lead R&D projects to validate data quality, establish ROI for new sports, and innovate novel biomechanical concepts. - Work with the development team to ensure data visualization and API egress methods meet client needs. - Perform rigorous testing when implementing development changes to production environments. Qualifications - Deep understanding of biomechanics principles, including inverse kinematics and dynamics, musculoskeletal modeling, and signal processing techniques. - Strong proficiency in Python, C++, or other open-source languages for data organization and interpretation. - Visual3D development and coding experience is strongly preferred. - Experience with linear algebra and mathematics relevant to biomechanics. - Expertise in statistical design for research purposes and a solid understanding of data science principles. - Proven experience using biomechanics for decision-making related to performance or health in a medical or sports context. - Proficiency with motion capture technology, including camera setup, calibration, and integration with third-party hardware like force plates. - Ability to carry technical conversations with engineers while also being able to explain "What is this analysis telling me?" to non-technical stakeholders like athletes and coaches. - A genuine passion for sports and the evolution of athlete performance metrics. Requirements - This is a remote-based position but some travel to company locations and client sites may be needed. Benefits - Competitive base salary ranging from $101,007 to $134,675. - Annual corporate bonus plan based on company performance (not guaranteed). - Comprehensive benefits package including healthcare benefits (medical, dental, and vision). - Paid medical leave. - 401k plan with matching company contributions. - Vacation time. - Education assistance. - Student loan assistance program. - Eighty hours of paid sick leave time annually. - Up to twelve weeks paid parental leave.