- Design and develop data pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems.
- Collaborate with data scientists and analysts to optimize models and algorithms for data quality, security, and governance.
- Integrate data from different sources, including databases, data warehouses, APIs, and external systems.
- Ensure data consistency and integrity during the integration process, performing data validation and cleaning as needed.
- Transform raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques.
- Optimize data pipelines and data processing workflows for performance, scalability, and efficiency.
- Monitor and tune data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance.
- Implement data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data.
- Take authority, responsibility, and accountability for exploiting the value of enterprise information assets and of the analytics used to render insights for decision making, automated decisions, and augmentation of human performance.
- Work with board members and other executives to establish the vision for managing data as a business asset.
- Establish the governance of data and algorithms used for analysis, analytical applications, and automated decision making.
- Proven project experience developing and maintaining data warehouses in big data solutions (Snowflake).
- Expert knowledge in Apache technologies such as Kafka, Airflow, and Spark to build scalable and efficient data pipelines.
- Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and BI.
- Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata.
- Strong ability in programming languages such as Java, Python, and C/C++.
- Ability in data science languages/tools such as SQL, R, SAS, or Excel.
- Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP) and modern data warehouse tools (Snowflake, Databricks).
- Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products.
- Ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options.
- Expert problem-solving skills, including debugging skills, allowing the determination of sources of issues in unfamiliar code or systems, and the ability to recognize and solve repetitive problems.
- Ability to translate among the languages used by executive, business, and IT stakeholders.
Data Engineer - Appleton, United States - The Boldt Company
Description
Information Technology
Appleton, WI• ID:
• Full-Time/Regular
HOW YOUR ROLE FITS INTO BOLDT:
The Data Engineer works with data to tackle business problems, builds/maintains the infrastructure to answer questions and improve processes, and helps to streamline our data analytics workflows. This IT role is responsible for building and maintaining pipelines for accessing raw data, managing & organizing data models for integrations and analytics projects & workflows. Success in this role is demonstrated by consistently centralizing high quality source data with little to no downtime, eliminating the manual work, increasing capacity, unlocking new potential business use cases by making data fresher, more reliable and more complete. Our Data Engineers are our technical data experts on the data and analytics team.
What you get to do:
Required Skills
What we expect from you:
·Bachelor's degree in computer science, data science, software engineering, information systems, or related qualitative field.
·Minimum of four years of work experience in data management disciplines, including data integration, modeling, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks.
Physical Requirements and Working Conditions:
While performing the duties of this job, the employee is frequently required to remain in a stationary position for up to eight hours. The employee occasionally is required to move to access people or operates a computer and other office equipment, such as a calculator, copy machine and computer printer. The ability to effectively communicate is required. The employee may occasionally move up to 15 pounds.
The working conditions of this positionrequires the employee to work inside an office environment. The environment for which this position functions may contain scents and fragrances. May be requested to work overtime and weekends.
The Boldt Company is an Equal Opportunity Employer .
Disclaimer: This job description is intended to be a summary of the primary essential duties and responsibilities of this position. The job description is not intended to be inclusive of all duties an individual in this position might be asked to perform or all the qualifications that may be required either now or in the future. Other duties, responsibilities and activities may be assigned or changed at any time.
Individuals in this role may be subject to annual Motor Vehicle Records check. Outcome of any MVR checks conducted may negatively impact the persons' ability to participate in any vehicle program provided by the company, including but not limited to the ability to drive a personal vehicle on behalf of the Boldt Company or rent a vehicle through the Boldt Company travel provider, for a period of up to 1 year.