Technical Lead Job Specification
This job specification highlights the core activities and skills essential for Technical Leads (TLs) working with the Quantexa Platform. For Technical Leads working with the Quantexa Platform, the tools, responsibilities, and expertise recommended to meet industry standards are outlined. For Hiring Managers, it serves as a framework for defining role requirements when recruiting candidates with Quantexa experience. Important Note: These guidelines are for reference only, and companies may have additional or specific expectations for roles. Equivalent Roles: Staff/Principal Engineer Technical Manager Day-to-Day Activities Leading and mentoring a team of junior data engineers within an agile framework. Writing efficient, fault-tolerant, production-level code for your deployment. Collaborating with Solution Architects to champion solutions and standards for complex big data challenges. Ensuring best practices are followed within the team. Advising colleagues on technical concepts and translating them into actionable insights for decision-making. Supporting development and operations by ensuring high-quality, operationally stable systems. Recommended Quantexa Skills & Experience Proven experience helping to implement multiple Quantexa projects, with a strong understanding of Quantexa architecture and components. Experience leading a standard team through a full Quantexa project lifecycle, including upgrades. Familiar with all Quantexa components and can design solutions optimally using the latest Quantexa features. Familiar with the tuning methodologies for ER, ETL performance, task loading. Recommended Technical Skills Proficiency in programming languages, particularly Scala, Java, Python, or similar. Experience with modern development tools and processes (e.g., Git, Gradle, Nexus) and automation/DevOps technologies (e.g., Jenkins, Docker, Bash scripting). Knowledge of cloud platforms (Google Cloud, Azure, AWS) and big data technologies (Spark, Hadoop, Elasticsearch). Experience in building and deploying production-level data processing systems with a focus on operational stability. Understanding of testing frameworks and the ability to write unit and integration tests using libraries like ScalaTest. Expertise in designing scalable big data solutions and production-level data processing systems. Strong hands-on coding ability with a focus on fault-tolerant, efficient, and defensive programming. Proficient in setting up development workflows and managing complex technical initiatives. Familiarity with Agile practices, project management tools, and software lifecycle processes. Recommended Soft Skills Ability to lead, mentor, and support junior engineers and team members in a technical environment. Strong technical communication skills, especially for explaining complex technical concepts to non-technical stakeholders. Ability to work effectively with cross-functional teams. Capable of making decisions that improve the operational stability and efficiency of data systems. Clear and confident communicator, able to translate technical concepts for non-technical stakeholders. Significant cross-domain problem-solving experience and a demonstrated ability to navigate ambiguity. Skilled in growing junior team members through mentoring, feedback, and guidance. Strong problem-solving ability across domains, with a proactive approach to risk mitigation. Effective at managing competing priorities and navigating ambiguity. Recommended Leadership & Collaboration Skills Leads by example, fostering a collaborative and goal-oriented team environment. Sets clear expectations, makes informed decisions, and communicates transparently. Engages with stakeholders to align technical work with business value. Trusted advisor, with a focus on shared success. Read more about Technical Leads: Technical LeadSenior Data Engineer Job Specification
This job specification highlights the core activities and skills essential for Senior Data Engineers working with the Quantexa Platform. We recommend that Senior Data Engineers have at least four years of industry experience as a Data Engineer or in an equivalent role. For Senior Data Engineers working with the Quantexa Platform, the tools, responsibilities, and expertise recommended to meet industry standards are outlined. For Hiring Managers, it serves as a framework for defining role requirements when recruiting candidates with Quantexa experience. Important Note: These guidelines are for reference only, and companies may have additional or specific expectations for roles. Day-to-Day Activities Writing efficient, fault-tolerant, production-level code for your deployment. Building and managing end-to-end data pipelines. Advising colleagues on technical concepts and translating them into actionable insights for decision-making. Collaborating to develop and implement solutions for complex challenges. → Modified Mentoring junior team members and collaborating with stakeholders to develop and implement solutions, ensuring best practices are followed. Recommended Quantexa Skills & Experience Experience implementing any of the Quantexa modules. Technical & business understanding of how and why Quantexa solutions are implemented. Comfortable performing most of the Quantexa standard tasks, such as: Parsers tuning Entity Resolution Tuning Complex Scoring Decision Systems (previously Detection Packs) Data Packs Upgrades Entity Reporting Authentication and Authorization Recommended Technical Skills Experience independently shaping and executing solutions for initiatives and challenges. Ability to persist in the face of roadblocks, dispatching them efficiently, and escalating when required. Advanced Scala, Spark, and Git. Proficiency in programming languages, particularly Scala, Java, Python, or similar. Experience in building and deploying production-level data processing systems. Experience with modern development tools and processes (e.g., Git, Gradle, Nexus) and automation/DevOps technologies (e.g., Jenkins, Docker, Bash scripting). Knowledge of cloud platforms (Google Cloud, Azure, AWS) and big data technologies (Spark, Hadoop, Elasticsearch). Understanding of testing frameworks and the ability to write unit and integration tests using libraries like ScalaTest. Recommended Soft Skills Experience supporting or mentoring junior members within a team. Ability to identify and highlight risks, communicating them early; not just in your own work, but also what you notice in others’ work and during backlog refinement. Experience leading agile ceremonies. Ability to step in and cover Technical Leads (TLs) where needed with a strong understanding of their priorities and project plans. Problem-solving mindset with the ability to tackle complex challenges. Strong communication skills for articulating technical concepts. Adaptability to work in rapidly changing client environments. Read more about Senior Data Engineers.
