-
ID
#32214943 -
Salary
TBD -
Source
Bertrandt US -
Date
2022-01-21 -
Deadline
2022-03-22
Automotive Business Data Quality Engineer
Virginia, Herndon, 20170 Herndon USAVacancy expired!
Bertrandt - your trustworthy engineering partnerLooking for a career, not just a job? Want to join a dynamic team working for an international industry leader? Enjoy an energetic work atmosphere? Bertrandt US may be just what you have been looking for! The Bertrandt Group has been providing development solutions for the international automotive and aviation industries in Europe, China and the USA for more than 40 years. A total of around 13,000 employees at 53 locations guarantee extensive know-how, sustainable project solutions and a high level of customer orientation. Its main customers include the major manufacturers and numerous system suppliers.The Business Data Quality Engineer is part of the Data & Analytics team. In this role, the Business Data Quality Engineer works closely together with the data provision team on the technical side (Data Architects, Developers, Engineers) who are building ETLs, tables, structures etc. to onboard and manage data assets and the teams receiving data on the business side (Business Intelligence Specialists, Data Scientists) which require and consume data to support the creation of reporting, visualization, analytics and data services in general. The objective is to ensure usability of the data by defining and leveraging quality standards based on feedback and input from the data subject matter experts and automate data cleaning and cleansing procedures. Part of this task is to leverage existing tools to define and document data process flows and governance functions.Support data Migration & Conversion
Enable & support Data Analysis
Data Quality Management incl. standardized procedures
Uphold Data Governance standards
Customer focus: keep internal audience in mind when building processes (user input) and solution design (presentation layer of quality control process & monitoring)
Understand physical database structures (Schema, indexes, etc.)
Create database objects (tables, indexes, etc.)
Perform data analysis – source/ target data assets
Perform data migration plan analysis – source/ target data assets
Data migration results assessment – Data Quality evaluation, to include discrepancy analysis and resolution
Develop complex SQL and PL/SQL scripts
Tune SQL for improved performance
Work with data scientist to ensure time to market of analytics requests and trials by ensuring proper data formatting and data availability
Business Collaboration: work with stakeholders across the enterprise and members of the data science community to define data quality expectations, status of
quality based on data assets and assist in quality standardization of existing and new data assets
IT Collaboration: work with developers and architects to implement proper data quality process and quality measurement goals
Work cross-functional to define and automate data quality measurement and assurance process
Identify & detect data quality issues and prioritize fix across roadmap
Define data quality measurement system (e.g. certification of data sources based on quality standards)
Create awareness amongst stakeholders, partners and affiliates about importance of data quality and existing data quality management procedures
Create reports and analysis to define state of data quality by data asset
Leverage and enhance existing standards for data profiling and monitoring for data assets
Work with data owners and Customer 360, product 360 and operations 360 experts to ensure enablement and usability of enterprise data assets
Research, collect and inform practices and innovations for data quality management
Create technical documentation supporting sharing of understanding and flow of data quality management process
Leverage existing tools to document data related processes across the organization by working with respective stakeholders
Actively involve and leverage other team members of the Data & Analytics team to assist with deliverables and responsibilities
Identify data quality issues and root cause
Quantify issues and impact and work with IT delivery team on sustainable resolution
Define escalation process to resolve underlying data discrepancies by working with Data Steward
10+ years of experience
Required: B.S. + continued learning via e.g. MOOCs,
Desired: B.S. Communications, Business Analytics, Computer Science or degree in a discipline that fosters structured problem solving and creativity
Ability to triage and troubleshoot data consumption and data quality problems
Ability to timely identify and escalate issues/risks
Extensive knowledge + certification in following technologies:
Understand databases & structures (oracle, SAP, Hadoop)
Understanding of both batch and stream processes and tools e.g. Kafka, ETLs, SFTPs, APIs
Experience with end to end data testing &/or data analysis as well as knowledge of best practices & methodologies for data QA
Experience with scripting (Python, Perl, Ruby, bash, etc.)
Experience with REST based services and testing
Experience with JSON, CSV, and other data exchange formats (e.g., YAML)
Ability to develop test plans, test cases, test scripts and test results
Extensive knowledge + certification in following technologies: SQL, python, Informatica Data Quality, AXON, process and quality assurance, Six Sigma
Benefits:Complete and comprehensive benefits package including Med/Dent/Vision.
Employer paid STD/LTD/Life.
401k Retirement program.
Generous paid vacation/sick/holidays.
Creativity encouraged in a fun, friendly work environment.
ID: 2022-2011 External Company URL: http://www.bertrandt.com/en/
Vacancy expired!