As an Analytics Engineering Manager, you will lead a team of analytics engineers and collaborate closely with cross-functional stakeholders to enable data-driven decision-making within the organization. You will be responsible for managing the end-to-end analytics engineering process, including data collection, transformation, storage, and visualization. Your role will involve driving the adoption of best practices, and mentoring the team members to deliver high-quality analytics solutions.
Key Responsibilities:
Team Leadership and Management:
- Provide leadership, guidance, and mentorship to a team of analytics engineers.
- Set clear goals and expectations, and establish a collaborative and inclusive work environment.
- Foster professional growth and development of team members through regular feedback, coaching, and training opportunities.
- Manage resource allocation, workload prioritization, and project planning to ensure timely delivery of analytics solutions.
Analytics Infrastructure Development:
- Design and implement scalable data infrastructure, including data pipelines, data warehouses, and ETL processes to enable efficient data collection, storage, and retrieval.
- Collaborate with data platform engineering and IT teams to ensure data quality, integrity, and security throughout the analytics ecosystem.
- Evaluate and implement new technologies, tools, and frameworks to improve the efficiency and effectiveness of analytics engineering processes.
Data Transformation and Preparation:
- Define and enforce data transformation standards and best practices to ensure data consistency, accuracy, and usability.
- Oversee the development and maintenance of data transformation workflows, data cleansing techniques, and data validation processes.
- Collaborate with data scientists and analysts to understand their data requirements and provide guidance on data preparation and feature engineering.
Data Visualization and Reporting:
- Work closely with business stakeholders to understand their reporting and analytics needs.
- Collaborate with data visualization experts to design and develop interactive dashboards, reports, and visualizations that effectively communicate insights and enable self-service analytics.
- Ensure the availability and accessibility of timely and accurate data for reporting purposes.
Performance Monitoring and Optimization:
- Establish monitoring mechanisms and metrics to track the performance and reliability of the analytics infrastructure.
- Identify opportunities for performance optimization and scalability improvements, and implement necessary enhancements.
- Proactively address data quality issues and resolve technical challenges to ensure smooth and efficient analytics operations.
Collaboration and Stakeholder Management:
- Collaborate with cross-functional teams, including data scientists, business analysts, product managers, and executives to understand their analytics requirements and provide technical guidance.
- Act as a liaison between the analytics engineering team and other stakeholders, ensuring effective communication and alignment of goals and expectations.
- Present findings, insights, and recommendations to non-technical stakeholders in a clear and concise manner.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
- 7+ years of experience in analytics engineering or a similar role, with a proven track record of managing and delivering complex analytics projects.
- Strong technical expertise in data engineering, data modeling, and data architecture.
- Proficiency in programming languages such as Python, SQL, and experience with data manipulation tools (e.g., Spark, Hadoop).
- Familiarity with data visualization tools and platforms (e.g., Tableau, Power BI) and experience in designing intuitive dashboards and reports.
- Solid understanding of data governance, data quality, and data security principles.
- Strong leadership and people management skills, with the ability to inspire and motivate a team.
- Excellent communication and stakeholder management skills to effectively collaborate with technical and non-technical stakeholders.
- Strong problem-solving and analytical thinking abilities, with a focus on delivering practical and actionable insights.