In this role, you will design, build, test, and implement data engineering processes that support analytical and reporting solutions. You will also prepare data for data science outcomes, manage metadata structures, and focus on automation and timely delivery using agile methodologies.
Responsibilities
- Build technical data dictionaries and support business glossaries to support dataset analysis
- Perform data profiling and data analysis across source systems, manually maintained data, machine generated data, and target repositories
- Develop logical and physical data models for both OLTP and OLAP solutions
- Create and maintain data mapping specifications based on analysis results and functional requirements
- Execute data loads and data transformations using multiple tools and technologies
- Build automated ETL jobs based on data mapping specifications
- Maintain metadata structures that enable reusable ETL components
- Analyze reference datasets and become familiar with Master Data Management (MDM) tools
- Assess the impact of downstream systems and products
- Use deep dive data analysis to derive solutions and make recommendations
- Design and build Data Quality (DQ) rules
Requirements
- Bachelor’s degree from an accredited university or college with a minimum of 2 years of professional experience, or an Associate’s degree with a minimum of 5 years of professional experience, or a High School Diploma with a minimum of 7 years of professional experience
- Legal authorization to work in the U.S. required; no employment visa sponsorship will be provided for this job, now or in the future
- Exposure to industry standard data modeling tools (for example, ERWin, ER Studio, etc.)
- Exposure to ETL tools such as Informatica or Talend
- Exposure to data catalog, automated data discovery, and data lineage tools (for example, Alation, Collibra, TAMR, etc.)
- Hands-on experience with programming languages including Java, Python, or Scala
- Hands-on experience writing SQL scripts for Oracle, MySQL, PostgreSQL, or HiveQL
- Experience with Big Data technologies such as Hadoop, Spark, Hive, or NoSQL database engines (for example, Cassandra or HBase)
- Exposure to unstructured datasets and ability to work with XML and JSON file formats
- Ability to conduct exploratory data analysis and generate visual summaries, with proactive identification of data quality issues
Eligible Experience
Military experience is considered equivalent to professional experience.
U.S. Export-Control Requirements
- This role requires access to U.S. export-controlled information
- Employment is contingent on the ability to prove you meet the status of a U.S. Person, including: U.S. lawful permanent resident, U.S. Citizen, or granted asylee or refugee status (a protected individual under the Immigration and Naturalization Act, 8 U.S.C. 1324b(a)(3))
Location and Work Setting
Dayton, OH, onsite.
Relevant Technologies
ERWin, ER Studio, Informatica, Talend, Alation, Collibra, TAMR, Java, Python, Scala, SQL, Oracle, MySQL, PostgreSQL, HiveQL, Hadoop, Spark, Hive, Cassandra, HBase, XML, JSON.
