Senior Data Engineer

America First Credit Union•Riverdale, UT

18h

About The Position

This position is responsible for aiding operational areas of the organization leveraging both internal and external data assets to achieve business insights, gain deeper understanding of member needs, and enhance tactical and strategic decision making. The Data Engineer position will support the architecture and systems that support data movement within the organization in both Linux and Windows environments, including managing the software that runs in those environments. Collaborates with data science team, software developers, business analysts, and data engineering to extract transactional, historical, analytical, behavioral and predictive data sets by building data pipelines from ever increasing data resources. Understands progressive statistical, programmatic, and analytical approaches to business hypotheses as it applies to available data. Aids business owners & data science team in the interpretation of source data and associated business data pipelines. Requires a solid understanding of both the technical and business aspects of Data Science and business analytics. Requires full software development life cycle experience within various analytical architectures, including piloting models and processes, architecting underlying data design, and model/process operationalization. Models will be deployed using agile methodologies to ensure timely and relevant delivery. Will be required to explore internal and external data sources to identify useful structures within the data that were/are previously unknown to the business. Should have a strong understanding of relational and dimensional modeling to facilitate data wrangling, model operationalization, and exploration of data. Responsible for adhering to corporate data governance policy and controls to ensure the accuracy, timeliness and confidentiality of resources under management. Must be able to work with users from all levels of management in developing and implement operational and strategic analytics. The Data Engineer’s primary focus will be on operationalization of data pipelines to facilitate use of novel and optimized data set products by a variety of end users using a variety of data transformation tools.

Requirements

Bachelor of Science degree in information technology, computer science, statistics, or related business degree with equivalent experience of 10+ years.
Master of Science in information technology, computer science, statistics, or related degree with equivalent experience of 5+ years.
Minimum of 7 years experience in designing, developing and implementing Data solutions.
Must have advanced SQL abilities, experience with both Oracle and Microsoft desired.
Must have advanced programming experience with Python
Must have experience with Linux.
Experience developing business analytical solutions in large or midsize companies.
Must be able to manage multiple tasks simultaneously and react to problems quickly.
Must be able to translate concepts and directions into practical solutions.
Understand data collection, streaming, preparation, analysis, visualization, modeling, algorithm integration, evaluation, optimization within an implementation context.

Nice To Haves

Experience with a variety of ETL tools is desired, Airflow, SSIS, Informatica, dbt, etc.
Experience with Anaconda; Kafka; RabbitMQ; Jupyter Notebook; Tableau desired
Understanding of the financial services industry desired.
Experience with dashboard design and delivery desired
Must have development experience with various data management technology; NoSQL; relational database; message broker; multi-dimensional database; and design architecture.

Responsibilities

Manage Installation, patching, upgrading, and administration of software systems that support data pipelines. This includes ETL platforms (Airflow, SSIS) , data quality platforms Great Expectations), distributed data processing systems (Hopsworks, Polar), and streaming platforms ( Kafka , RabbitMQ.)
Develop data pipelines to support operational implementation of Data Science and analytical models.
Ensure all security, documentation, governance, and compliance standards are met.
Oversee development of small reporting layer on top of analytical models to ensure accountability and insight into models’ performance and impact.
Perform DevOps and orchestration around supporting data marts and analytical processes.
Mentor Data Engineer I, II, III levels to train them on best practices and optimal technology usage.
Work with management regarding forecasting, planning, and implementation of used and future technologies leveraged to support data engineering processes.
Engineer each solution with appropriate kinds of technology, with optimized performance.
Execute analytics solution engineering strategy, requirements, and adapt processes as needed.
Monitor and secure usage of data while tracking platform product performance.
Advise and collaborate in internal partnerships to deliver accurate, available, and accessible API services.
Identifies potential concerns based on projections of current trends.
Contribute to Credit Union culture by keeping a positive attitude and growing relationships