Job overview and responsibilities
The Data Analytics Manager is a data driven leader with a passion for data and analytics, the willingness to dig deep into details, and the ability to assess the big picture and identify process improvement. Developing and maintaining strong relationships with key stakeholders across Digital Technology and Product teams with a good understanding of the business, as well as leading, coaching, training, and motivating a talented team are keys to success in this role. This team would be integral to interpret data gathered from various sources for patterns and trends, turning it into information which improves Operational Excellence (OX). This role requires a communicator with passion for finding the signal in data and ability to come up with improvements to applications and metrics to be measured. Should be comfortable enough to communicate with the developers, platform teams, business analysts, user experience and the leadership in influencing change based on the data.
This role:
- Is crucial in translating complex data into actionable insights that influence business strategy, optimize operations, and drive growth
- Is responsible for overseeing the entire analytics lifecycle, from data collection and processing to analysis, reporting, and presentation of findings to stakeholders across various departments
- Develops streamlined and comprehensive data analytics workstreams
- Areas of focus will include, but are not limited to:
- Data Engineering
- Data Analytics
- Product Management
- Impact Analysis
- Error patterns, top factors contributing to errors
- Identify, design, and implement internal process improvements\: recommendations for performance and greater scalability
- Modeling and coding of data
- Manager for 3-4 data analysts\: provides technical guidance and subject matter expertise to the team
- Partner with key stakeholders to understand their data needs, define key performance indicators (KPIs), and translate business questions into analytical problems
- Lead analysis of new platform updates and application releases, learn the existing application/systems to research system performance, dig into errors, response time, service logs, define new data collection and tagging, create universal dashboards
- Responsible for the supervising the prioritization and planning efforts for their respective portfolio
- Communicate and share updates with senior leadership, along with putting together regular presentations
- Technical Expertise:
- Manage the product roadmap of data products, including development and deployment of data pipelines and visualizations that convert data into actionable insights.
- Working knowledge of incorporating Gen-AI into Analytics & Data Engineering for generating tangible benefits to the organization
- Ensure seamless integration of BI solutions with current systems and data sources.
- Keep abreast of industry developments, tools, and best practices in BI and data analytics
- Lead reviews of models, solution strategies, and code with the team to leverage its collective experience and reviews of solutions with business/product management teams to ensure that they are acceptable.
Qualifications
What’s needed to succeed (Minimum Qualifications):
What will help you propel from the pack (Preferred Qualifications):
- Master's degree in Information Systems, Aviation management or related degree, MBA
- Google Data Analytics Professional Certificate, Power BI Data Analyst Associate, AWS Certified Data Analytics, Enterprise Data Warehouse certifications, Palantir, Client Side performance metrics tools e.g. Quantum Metrics
- 3+ years in a manager role
- Fortune 500 experience
- Experience with DataDog / AppD / Kibana is a big plus
- Experience with Enterprise monitoring systems is a plus
- Experience with Palantir Foundry, Microsoft SQL Server Management Studio
- Previous airline or travel industry experience is a plus
- Experience with AWS - Redshift, Quicksight, Athena
- Experience with Big Query
- Experience with Quantum Metrics and Akamai, Technologies and languages\: Python, Spark, R, etc.
- Continuous integration & delivery using Agile methodologies
- Data Engineering experience