Summary:

Barr Engineering Co. seeks a data engineering consultant to help us build and expand our newly formed Environmental Management Analytics and Information Systems team. Your primary focus will be to support the data engineering and architectural needs of our external client projects. When not building end-to-end solutions for external projects, you will assist Barr's internal Information Systems team in advancing our rapidly maturing and analytics data-related capabilities. You will use the latest cloud-based tools to design and build solutions for IoT and telemetry-based instrumentation, a cloud-based data lake, API integration of internal and external platforms, and many other tools to support various fascinating engineering efforts.

Barr works on thousands of client projects each year. The data-related needs of these projects vary significantly. This role is well-suited for a problem-solver who is passionate about data and wants to work in an environment with significant growth opportunities. You will be given the opportunity to learn and develop your technological skills across various platforms and help drive the future of our Environmental Management Analytics and Information Systems team.

Responsibilities include:

• Support the data engineering, management, and governance needs of an array of engineering and scientific projects for our external clients

• Identify, design, and implement process improvements, re-designing infrastructure for greater scalability, optimize data delivery, and automate manual processes

• Support the acquisition and processing of large datasets generated by IoT and instrumentation

• Integrate systems and data sources through APIs and ETL tools

• Support data science, system implementation, and system development efforts

• Design data flows and pipelines to optimally extract, transform, and store data using on-prem and cloud technologies

• Advance the design and development of Barr's enterprise data warehouse, data lake, dashboarding, and self-service reporting ecosystem using the Microsoft Business Intelligence toolset (SQL Server, SSIS, SSAS tabular, Power BI, Azure)

• Lead the process of engaging business analysts and business unit staff to elicit and document data requirements

• Write complex queries

• Design and develop database objects (databases, tables, views, stored procedures, etc.) within a normalized and dimensional data warehouse environment

• Develop auditing and quality assurance practices to help ensure the accuracy of the data warehouse and reporting

• Mentor business unit staff to advance their data capabilities and understanding

Minimum Qualifications:

• Bachelor's degree in computer science, information systems, a related field, or equivalent work experience

• Three years of experience in a data engineering, database administrator, or business intelligence role

• Experience developing data warehouse and data lake tools for business purposes

• Experience supporting the development of analytical tools for business purposes

• High proficiency in SQL queries

• Experience with Python developer

• Experience developing Rest APIs

• Experience with ETL and data modeling technologies (e.g., SSIS, Data Factory, SSAS - Tabular)

• Strong understanding of security in an integrated on-premises and cloud-based data environment

• Proficient in working with diverse data types, including structured, semi-structured, and unstructured formats

• Proficiency with Azure technologies such as Data Factory, Data Lake, and Azure Analysis Services

• Experience leading requirement-gathering efforts for data engineering projects

• Strong organizational skills, including the ability to plan, monitor, and follow through on work commitments and confirm priorities with stakeholders

• High level of commitment to delivering exceptional client service

• Excellent written and oral communication skills

• Strong analytical and problem-solving skills

• Possession of a valid driver's license and acceptable driving record

• Legal authorization to work in the United States without the need for sponsorship from Barr, now or in the future

Preferred Qualifications:

• One or more Microsoft Azure certifications

• Experience with databricks

• Experience developing in data visualization platforms such as Power BI, Tableau, or related platforms

• Knowledge of data warehouse development processes and techniques, including dimensional modeling

• Familiarity with AI, Machine Learning, and Data Science concepts and tools

• Experience working with large volumes of streaming data

• Knowledge of environmental data (e.g. air quality, water quality, geological, remote monitoring sensors) and environmental data systems (e.g. EQuIS, GIS, EMIS)

A hybrid or remote work arrangement may be considered for this position. A hybrid arrangement refers to splitting time worked between a Barr office and a home office; a remote arrangement refers working primarily from a home office. This position can be based out of Barr's Minneapolis, Minnesota, office. Remote arrangements will be considered based on candidate qualifications, location requirements, and Barr's needs.

Colorado Applicants Only:

The anticipated base salary range for this position is $100,000-$120,000. Compensation will vary based on experience, education, skill level, and other compensable factors. Employees in this position may also be eligible for a discretionary cash bonus. Our compensation comes in more ways than traditional base salary, and we believe that when all those elements are combined, our compensation is a competitive part of the total value proposition of working at Barr.

Benefits:

People report that they stay at Barr because of the camaraderie and career opportunities. Another draw is our competitive package of employee benefits, which includes professional development funding, 401(k) retirement savings plan, employee stock ownership plan (ESOP) participation, medical and dental insurance, life insurance, disability and accidental death insurance, flexible spending accounts for healthcare and dependent care expenses, paid holidays, paid time off, and compensatory time for exempt/salaried staff (time off or pay for extra time worked).

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