As the first hire for their data team, the Lead Data Analytics Engineer will play a pivotal role in establishing our data analytics capabilities. You will be responsible for designing, building, and maintaining our data infrastructure, as well as leading the charge in turning raw data into actionable insights. Your expertise in Python and SQL will be crucial as you manipulate and analyze complex datasets to inform key business decisions, optimize processes, and enhance our product offerings.
Key Responsibilities:
- Design and implement the company’s data architecture, laying the foundation for scalable data collection, storage, and analysis.
- Develop ETL (Extract, Transform, Load) processes to ensure data is clean, accurate, and readily accessible for analysis.
- Select and integrate appropriate data tools and platforms, balancing current needs with future scalability.
- Utilize Python for data manipulation, analysis, and the creation of algorithms that drive business insights and innovation.
- Write and optimize complex SQL queries to extract, transform, and analyze data from various sources, ensuring data integrity and accuracy.
- Lead the development of analytics models and dashboards that provide actionable insights to key stakeholders.
- Serve as the primary point of contact for all data-related initiatives, collaborating with cross-functional teams to identify and prioritize analytics projects.
- Establish best practices for data management, analysis, and reporting, fostering a data-driven culture across the organization.
- Develop and maintain key performance indicators (KPIs) and metrics to monitor the company’s performance, customer engagement, and operational efficiency.
- Create and present regular reports and dashboards that communicate insights to non-technical stakeholders, driving informed decision-making across the company.
- Continuously analyze and refine our data processes and tools, ensuring that we remain at the cutting edge of data analytics.
Qualifications:
- 5+ years of experience in data analytics, data engineering, or a related field, with a strong emphasis on Python and SQL.
- Experience in a start-up or high-growth environment, with a proven track record of building data solutions from scratch.
- Experience in the events management industry or a similar domain is a plus but not required.
- Advanced proficiency in Python for data manipulation, analysis, and automation.
- Expert in SQL, with deep experience in database management, query optimization, and handling large datasets.
- Familiarity with data visualization tools such as Tableau, Power BI, or similar platforms.
- Experience with cloud-based data platforms (e.g., AWS, Google Cloud, Azure) and big data technologies is desirable.
- Strong understanding of statistical analysis, machine learning, and data modeling techniques.