Date Posted:2023-09-11Country:United States of AmericaLocation:PW100: East Hartford 400 Main Street, East Hartford, CT, 06118 USAPosition Role Type:HybridPratt & Whitney is working to once again, transform the future of flight—designing, building, and servicing engines unlike any the world has ever seen. And because transformation begins from within, we’re seeking the people to drive it. So, calling all curious.Come ready to explore and you’ll find a place where your talent takes flight—beyond the borders of title, a country or your comfort zone. Bring your passion and commitment and we’ll welcome you into a tight-knit team that takes our mission personally. Channel your drive to make a difference into shaping an organization and an industry that’s evolving fast to the future.Innovation through diversity of thought. At Pratt & Whitney, we believe diversity of thought enables creativity, innovation, and a foundation for inclusion. By fostering an inclusive culture, we accept a shared accountability and responsibility to recognize, sponsor, coach, hire and promote talent equally. We welcome our employees to be their whole - best - selves at work because trust, respect and integrity, are a part of our DNA.At Pratt & Whitney, the difference you make is on display every day. Just look up. Are you ready to go beyond?Job Summary:The F135 Data quality Team is seeking a motivated self-starter for Senior Analyst position. The candidate will work in East Hartford, CT, supporting the integration of F135 propulsion system into the Autonomic Logistics Information System (ALIS).As a F135 Data Quality Senior Analyst, you will play a vital role in ensuring the accuracy, reliability, and integrity of data related to the F135 engine program. You will be responsible for analyzing, validating, and enhancing data processes to support critical decision-making for the program. Your expertise will help identify data quality issues, develop strategies for improvement, and maintain data integrity to ensure the F135 program's success.Key Responsibilities:
Analyze large datasets and perform data profiling to identify inconsistencies, errors, and data quality issues within the F135 engine program's data ecosystem.
Develop and implement data validation procedures to ensure the accuracy and completeness of data collected from various sources and systems.
Collaborate with cross-functional teams to enrich data by incorporating additional attributes and relevant information to improve the overall data quality and utility.
Implement data governance policies, standards, and best practices to maintain data integrity and adhere to industry regulations. Investigate and resolve data-related issues and discrepancies in a timely manner, communicating findings to relevant stakeholders.
Continuously evaluate existing data processes and propose enhancements to optimize data quality and streamline data management procedures.
Monitor data quality metrics and perform regular audits to ensure adherence to established data quality standards and guidelines and prepare comprehensive reports and documentation on data quality findings, recommendations, and actions taken.
Bachelor’s degree in computer science, Data Science, Information Management, or a related field.
A minimum of 5 years of experience in data analysis, data quality management, data querying and manipulation using SQL, Python, and statistical analysis software, as well as experience with markup language such as XML.
U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.
Advanced degrees or certifications are a plus.
Strong analytical and problem-solving skills to identify data issues and propose effective solutions, as well as attention to detail to ensure accuracy and precision in data validation and analysis.
Excellent written and verbal communication skills to convey complex data quality concepts to both technical and non-technical stakeholders.
Experienced with MS office Suites.
Proven ability to work collaboratively in a cross-functional team environment.
Ability to adapt to evolving data quality requirements and technological advancements in the field.