Title: Senior Data Engineer
Location Tullahoma, TN
Salary: $120,000 - 140,000
Contact: Paul Chatlos, pchatlos@smithhanley.com
Senior Data Engineer Job Duties:
-Development and implement data-engineering strategies and programs.
-Utilize test data sources to optimize data analytics at company and suggest ways which insights obtained might be used to inform testing sustainment and operational strategies.
-Automate manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
-Utilize machine learning tools to select features, create, and optimize classifiers.
-Define & develop approaches and demonstrate abilities to mine and analyze data from databases to drive optimization and improvement of data collected at company
-Identify and assess the effectiveness of data engineering, data sources and data gathering techniques.
-Utilize applicable experience in "big data", analytics, algorithmic, custom data models, algorithms and/or machine learning approaches to help extract data that will help drive engineering decisions.
-Coordinate with different multidisciplinary teams to implement models and monitor outcomes.
-Define & develop processes and tools to monitor and analyze model performance and data accuracy.
-Define & develop the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and 'big data' technologies.
-It is a condition of employment to wear company issued PPE (Personal Protective Equipment) in accordance with supervisory direction and company policy.
-Identify and complete projects associated to data-engineering.
-Performs other related duties as required.
Senior Data Engineer Basic Qualifications:
-B.S. in Computer Science, Statistics, Mathematics, Engineering or another relevant engineering field from an accredited university program plus a minimum of 6 to 14 years of progressive and relevant experience.
-Current U.S. Citizenship is required.
Senior Data Engineer Preferred Qualifications
-Master's or PhD degree in Computer Science, Statistics, Mathematics, Physics, Engineering or another relevant engineering field from an accredited university program.
-Experience with development lifecycle methodologies such as Agile DevSecOps.
-Experience with data scripting language software like Python, Java, C++, or Ruby and SQL.
-Experience with data extraction tools and processes, data ingestion, ETL, data mining, API's and data warehousing.
-Demonstrated experience in a data engineering role.
-Experience working with and creating data architectures.
-Knowledge of a variety of machine learning techniques and their real-world advantages/drawbacks.
-Coding knowledge and experience with multiple languages
