Data & Analytics Engineer

As a Data & Analytics Engineer at Cybit, your primary responsibilities will include assisting clients throughout their Data & Analytics projects, using tools like Qlik Sense and Power BI. You’ll handle tasks such as data loading, cloud migration, dashboard creation, and system troubleshooting. Your role is essential in ensuring clients achieve a deep understanding of their business analytics, while also supporting training sessions to empower end-users.

To thrive as a Data & Analytics Engineer at Cybit, candidates should have a good knowledge of Qlik Sense or QlikView, a strong understanding of core data concepts, and proven experience querying databases using Microsoft SQL Server. Additionally, project delivery experience and stakeholder management skills are important, along with excellent communication abilities to engage with clients effectively.

The Data & Analytics Engineer role at Cybit serves as a stepping stone towards becoming a knowledgeable Data & Analytics Consultant. The position provides in-depth hands-on experience and access to professional development resources, allowing you to expand your technical skills, enhance your consultancy capabilities, and potentially progress within the organization as you build relationships with clients.

In the Data & Analytics Engineer role at Cybit, you will primarily work with Qlik Sense and Power BI for dashboard creation and data visualization. Additionally, familiarity with Microsoft SQL Server for database querying and an interest in learning other tools such as Azure Data Factory will be beneficial. Cybit encourages its engineers to upskill in various Data & Analytics platforms to enhance client offerings.

Cybit offers a comprehensive benefits package for its Data & Analytics Engineers, including a bonus scheme, a pension plan, 33 days annual leave (with the option to purchase more), a healthcare cash plan, electric car and cycle-to-work schemes, and an employee assistance program. The emphasis is on creating a supportive environment that promotes work-life balance and career growth.

When troubleshooting data visualization solutions, start by reproducing the issue while reviewing log files, error messages, and system performance metrics. Organize your troubleshooting process logically, documenting each step, and consult with team members to leverage collective expertise. Communication with the client is key to understanding their concerns fully.

In discussing your experience with data migration projects, focus on the steps you took, tools you utilized, and any challenges you overcame. Highlight a specific project, mentioning the scope, your role, the technologies employed, and the outcome. This will showcase your understanding of data migration processes and your capacity to deliver results effectively.

To gather requirements effectively, I would initiate discussions with stakeholders to identify their goals and challenges. Active listening is key; I would ask clarifying questions to ensure understanding while taking detailed notes. Creating diagrams or mock-ups can also facilitate better communication of their analytical needs, leading to a more successful project outcome.

I prefer using Qlik Sense for data analysis due to its intuitive interface and powerful visualization capabilities. Additionally, Power BI is also great for creating compelling dashboards. My choice often depends on the specific requirements of the project. Being adaptable and familiar with multiple tools ensures I can choose the right one for each client’s needs.

In a previous project, conflicting stakeholder priorities emerged, requiring me to facilitate a meeting to align everyone’s expectations. By establishing common goals and prioritizing needs based on project impact, I was able to manage their conflicts effectively. This experience taught me the importance of proactive communication and relationship-building in project management.

To ensure data accuracy and integrity, I implement thorough validation checks at each stage of data handling, using write-back features and consistency checks. Regular communication with data sources and stakeholders is also essential, as it helps identify discrepancies and establish corrective actions swiftly.

I thrive in collaborative project environments and view them as opportunities for peer learning. I've frequently worked alongside data analysts and consultants, coordinating tasks and sharing insights in real-time. Engaging different perspectives enhances project quality, and I actively contribute to a supportive atmosphere while securing positive outcomes.

I am proficient in querying Microsoft SQL Server, having utilized it extensively for data extraction, transformation, and loading (ETL) tasks. I understand how to write complex queries, perform data aggregations, and optimize queries for performance, ensuring that my data analyses are both timely and effective.

I keep up-to-date with advancements in data analytics tools and technology through online courses, webinars, and participation in relevant forums. I also follow industry leaders and subscribe to newsletters. Continuous learning is crucial in this fast-evolving field, and I’m committed to expanding my knowledge and skills.

A Data & Analytics Engineer plays a pivotal role in a team by acting as a technical bridge between data and business insights. They ensure that data strategies align with business goals, paving the way for informed decisions. By providing accurate data analytics, they enhance operational efficiency and drive continuous improvement across the organization.