Lead Data Analyst

Qualifications & Experience

Qualifications:

• Degree or Honours (12+3 or equivalent) In a relevant field such as Computer Science, Computational Mathematics, Computer Engineering, or Software Engineering.
• Specialization or electives in a Data & Analytics field (e.g. Data Warehousing, Data Science, Business Intelligence) a nice-to-have.
  

Experiences

• 5+ years in Data Analysis experience (Fewer years’ experience will be considered for Masters degree holders)
• Minimum 5+ years conducting data analysis tasks (e.g. source system identification, data dictionary/metadata collection, data profiling, source-to-target mapping)
• Proven track record developing and maintaining data documentation artifacts in organizations of similar size and complexity within project deadlines
• Proven track record developing templates for organizing data analysis output
• Deep expertise in business transformation rules and understanding of data solution designs
• Experience building conceptual, logical, and physical data models
• Experience writing complex SQL queries to analyze data and provide results to business users or project team members
• Experience with building information designs for data-centric projects on two or more of the following (preferably within an airline industry): Data Warehouses, Big Data Environments for Analytics, Data API, Business Intelligence Solutions
• Exposure to data governance or business intelligence tools (e.g. Collibra, Snowflake, Microstrategy, Power BI) is a nice-to-have
• Airline industry experience strongly preferred (or expertise in a supporting function such as HR or Finance); needs to understand the business domains well to conduct data modeling and analysis activities.
  

Knowledge/Skills

• Excellent communicator; able to communicate rationale, approaches, and complex data models to business stakeholders, peers, and management.
• Operates with a “You Code It, You Own It” mindset (i.e. supports the products they build.
• Demonstrated problem-solver; able to design and document solutions independently.
• Strong work ethic, being results-oriented, and accuracy/attention to detail are critical.
• Demonstrated initiative, able to work both independently and as a team member.
• Team player; able to collaborate with others to remove blockers, solve complex data problems, and debug/resolve issues.
• Self-starter and has a passion for exploring and learning new technologies, especially those in the Enterprise Data & Analytics space.
• Able to deliver solutions (and associated value) iteratively.
• Is accountable and displays a positive attitude.
  

Key Technologies/Tools

Big Data & Distributed Processing: Querying HDFS or ADLS file storage systems, with tools such as Hive or H-Base, ElasticSearch, Experience with AVRO / PARQUET file formats nice-to-have

Data Analysis, Modelling and Reporting: SQL, Snowflake, Data Vault 2.0, MicroStrategy, Power BI