Lead, Data Analytics, Digital Enterprise Services

The Lead, Data Analytics at Otto Aviation is responsible for developing a comprehensive data strategy, designing scalable data architectures, and leading the development of analytics solutions. You will collaborate with engineering and manufacturing teams, enforce data governance policies, and create interactive dashboards to communicate insights effectively.

Candidates for the Lead, Data Analytics role at Otto Aviation should hold a Bachelor’s degree in Data Science, Computer Science, or a related field. Additionally, over ten years in data analytics or engineering experience is necessary, along with expertise in tools such as Tableau, SQL, and cloud platforms like AWS or Azure.

Essential technical skills for the Lead, Data Analytics position at Otto Aviation include proficiency with data integration tools such as Talend and Informatica, experience with ETL processes, and the ability to work with analytics platforms like Tableau and Python libraries. Familiarity with machine learning frameworks and cloud solutions is also crucial.

The Lead, Data Analytics plays a pivotal role in Otto Aviation's digital transformation by implementing data governance policies, building scalable data architectures, and driving the development of advanced analytics solutions that provide actionable insights, thus facilitating data-driven decision-making across the organization.

A successful Lead, Data Analytics at Otto Aviation exhibits self-motivation, strong interpersonal and communication skills, and excellent critical thinking abilities. Additionally, a collaborative mindset and the capability to innovate and propose improvements are essential for contributing to the company's goals.

In my previous roles, I designed data architectures that integrated multiple systems, ensuring streamlined data flow. I utilized technologies like ETL tools and cloud services to create scalable solutions that met organizational needs.

I generally adopt a framework that establishes clear policies regarding data quality, security, and compliance. I ensure that stakeholders are regularly trained and informed to maintain high standards across all data-related operations.

I believe in establishing strong communication channels and understanding the unique data needs of different teams. Regular meetings and collaborative projects help bridge any gaps and promote a culture of shared goals.

I’ve led the implementation of predictive modeling and created real-time dashboards that provided insights into key performance metrics, thereby allowing teams to make informed, data-driven decisions.

I am proficient in Tableau and Power BI, and I use these tools to create interactive dashboards that convey complex data insights in user-friendly formats for different stakeholders.

In a previous project, I encountered fragmented data sources. I tackled this by developing an ETL pipeline that integrated the data, ensuring it was cleaned and consolidated for analysis, effectively resolving the issue.

I regularly engage with online courses, webinars, and industry forums. Networking with peers and attending tech conferences helps me stay informed about emerging technologies and methodologies.

I have hands-on experience using TensorFlow for building predictive models and Scikit-learn for data preprocessing and model evaluation, enabling effective data analytics solutions.

I focus on understanding my audience's needs and tailor my presentations to suit their level of expertise. Visual aids and storytelling techniques help in making complex data easier to understand.

I am motivated by the ability to use data to solve complex problems and drive business improvements. Seeing direct results from my analytics efforts keeps me engaged and passionate about my work.