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Data Engineer Senior

Employer
Bremer Bank
Location
Lake Elmo
Salary
Competitive

View more

Industry
Technology
Role
Engineer
Job Type
Long-Term
Hours
Full Time

The Senior Data Engineer designs robust, scalable solutions and data pipelines to automate the ingestion, processing and delivery of all types of data: structured and unstructured, batch, and Real Time streaming data. He/She will use their analytical, programming and technical skills to ensure that data ingestion pipelines are scalable, repeatable, secure, and can serve multiple users within Bremer. He/She will facilitate acquiring data from a variety of different sources, getting it in the right formats, assuring that it adheres to data quality standards, and assuring that users can get that data quickly.

The role exists to improve and extend our data processing platforms, including: Build and maintain data pipelines, to clean and process data; Tag and store source information and metadata in a way that will allow us to easily filter and search based on our project demand; Developing and applying methods of data collection, processing, and analyzing large volumes of data to build and enhance products, processes, and systems; Iterate and improve upon a learning system, facilitating the integration and matching of data with requirements, refining models, procedures and modules, learners, and experiment with new approaches; Take ownership of projects, laying the foundation of great code yourself and helping others around you to code to those standards. Work on new products as well on feature enhancements of existing products.

The role's core responsibilities include:

Design and development of key data pipelines and analytic capabilities

Analyzing and solving complex business problems, breaking down the work into actionable tasks

Consistently improving and optimizing data models to achieve peak performance across the entire analytics platform

Thought leadership, creation, and execution of the analytics platform's capabilities

This role functions as a core member of an agile team supporting strategic initiatives relying on data to solve complex problems. The Senior Data Engineer is responsible for the software platforms that provides insight from raw data and handles diverse sources of data seamlessly. This role will be responsible for understanding and applying standard and emerging technologies to solve complex business problems leveraging data.

Qualifications:

A combination of education and experience generally attained through a bachelor degree in Computer Science or Engineering and 7 or more years of experience with data management technologies, Business Intelligence technologies, design strategies, and experience with one or more advanced analytics tools. The Senior Data Engineer requires substantial expertise in a broad range of software development and programming fields. It is required to have knowledge of data analysis, end user requirements analysis, and business requirements analysis to develop a clear understanding of the business needs and to incorporate these needs into technical solutions. They have a solid understanding of physical data architecture and design principles. The ability to work well in a team environment is essential. Excellent communication skills and the ability to communicate in a clear and concise manner. Ability to work in a collaborative environment, follow pre-defined patterns and know when exceptions need to be made. Ability to define, communicate and improve development patterns. Understanding of impact analysis and how to properly identify potential consequences of a change.

Preferred Experience:

Strong expertise in software and data engineering and pipeline development.
Experienced in SQL and applying analytical languages like Python, R, Scala.
Experience working with large and complex data sets with multi-terabyte scale.
Experience with extract-transform-load (ETL) tools and software development platforms.
Experience in building data analytics solutions on Hadoop stack.
Experience with functional/event-driven programming.
Knowledge of SQL on Hadoop technologies such as Hive, Impala or Presto.
Knowledge of data analytics, visualization and governance.
Knowledge of development standards; ability to follow and implement as needed.
Knowledge of JVM languages such as Java, Groovy, or Scala.
Knowledge of operating big data production solutions at scale.
Demonstrated understanding of architecture and design of highly available/scalable distributed systems.
Familiarity with OLAP concepts and implementation.
Familiarity with data security standards and best practices for implementation.
Familiarity with Data Science concepts such as machine learning.
Familiarity with DataOps, and/or knowledge and experience with DevOps.
Familiarity of navigating the linux operating system.

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