Senior System Engineer Us Multinational Fortune 500 Airlines Firm Years T654
Job Description :
The Senior Developer will play a key role on the Enterprise Data Services team, responsible for transforming data from disparate systems to provide insights and analytics for business stakeholders. You’ll leverage cloud-based infrastructure to implement technology solutions that are scalable, resilient, and efficient. You will collaborate with Data Engineers, Data Analysts, DBAs, cross-functional teams, and business leaders. You will architect, design, implement and operate data engineering solutions, using Agile methodology, that empower users to make informed business decisions.
You are self-motivated, work independently, and have direct experience with all aspects of the software development life cycle, from design to deployment. You have a deep understanding of the full life data life cycle and the role that high-quality data plays across applications, machine learning, business analytics, and reporting. Strong candidates will exhibit solid critical thinking skills, the ability to synthesize complex problems, and a talent for transforming data to create solutions that add value to a myriad of business requirements.
You have the demonstrated ability to lead and take ownership of assigned technical projects in a fast-paced environment. Excellent written and speaking communication skills are required as we work in a collaborative cross-functional environment and interact with the full spectrum of business divisions. You demonstrate unsatiated curiosity and outstanding interpersonal “soft” skills. Ideal candidates have more than just knowledge or skill set, as they also have a “can do” mindset to find solutions.
· Bachelor of Science degree in Computer Science or equivalent.
· At least 3 + years of post-degree professional experience.
· Desired Airline industry experience
· Desired development experience building and maintaining ETL pipelines.
· Desired experience working with database technologies and data development such as Python, PLSQL, etc.
· Solid understanding of writing test cases to ensure data quality, reliability and high level of confidence.
· Track record of advancing new technologies to improve data quality and reliability.
· Continuously improve quality, efficiency, and scalability of data pipelines.
· Knowledge of working with queries/applications, including performance tuning, utilizing indexes, and materialized views to improve query performance.
· Identify necessary business rules for extracting data along with functional or technical risks related to data sources (e.g. Data latency, frequency, etc.)
· Develop initial queries for profiling data, validating analysis, testing assumptions, driving data quality assessment specifications, and define a path to deployment.
· Familiar with best practices for data ingestion and data design.