Data Engineer

Hollstadt Consulting; Minnesota; On-site; USD 83,000 - 110,000; Part time

Job summary

Hollstadt Consulting is seeking a data engineer to partner with data scientists and analysts in MN, SD, ND, IA or WI. The role focuses on framing problems, cleaning and preparing data, and delivering scalable data pipelines in a cloud-first environment.

Applicants should have 4+ years in analytics/data engineering and strong SQL, Python, and BI tool experience. Collaboration with stakeholders and cross-functional teams is essential.

Qualifications

• Bachelor’s degree in a quantitative field with 4+ years in analytics/data engineering or a Master’s degree.
• 5+ years of programming in SQL, Python, Java, R or Spark.
• Expert SQL with experience in Oracle, PostgreSQL, MySQL, or SQL Server.
• 4+ years in BI/Analytics tools such as Azure Data Factory, Synapse, Power BI, Databricks.
• Experience using Git and collaboration in teams.
• Strong communication and ability to work with business leaders and end users.

Responsibilities

• Frame problems with stakeholders and clean/integrate data.
• Design scalable data pipelines for ingestion, cleansing, transformation, and validation.
• Build data models and data flows across multiple pipelines.
• Work in a cloud-first data architecture and apply best practices.
• Adhere to data governance and compliance standards.
• Perform root-cause analysis and implement preventive fixes.
• Collaborate with developers to deliver measurable results at scale.

Skills

SQL

Python

Java

R

Spark

Git

Data governance

Team collaboration

Communication

Problem solving

Data modeling

Cloud data architecture

Education

Bachelor’s degree or Master’s in a quantitative field

Tools

Azure Data Factory

Synapse

Power BI

Databricks

Oracle

PostgreSQL

MySQL

SQL Server

Git

Job description

Location: Must be located in MN, SD, ND, IA, or WI to be considered

Rate: $70/hour W2

ACCOUNTABILITIES:

• All team members must champion and model our values of partnership, curiosity, compassion, integrity, and excellence, and must contribute to a culture of continuous learning.
• Work with stakeholders, data scientists and analysts to frame problems, clean and integrate data, and determine the best way to provision that data on demand
• Collaborate with other developers to design technology solutions that achieve measurable results at scale
• Build, design and develop scalable, efficient data pipeline processes to handle data ingestion, cleansing, transformation, integration, and validation required to provide access to prepared data sets for analysts and data scientists
• Have experience in a cloud-first modern data architectural environment, and consistently leverage associated standards and best practices
• Adhere to data governance standards to ensure that data modeling and data handling procedures are compliant with applicable laws and policies across data pipeline.
• Perform root cause analysis in response to detected problems/anomalies to identify the reason for alerts and implement advanced solutions that prevent recurring points of failure.
• Applies in-depth knowledge of the business to design a data model that is appropriate for the project and translates business requirements into design specification documents to model the flow and storage of data across multiple data pipelines.
• Identifies multiple, complex data sources and builds advanced code to extract raw data from identified upstream sources using query languages, tools, or machine learning algorithms, while assuring accuracy, validity, and reliability of the data across the pipeline.
• Formulate techniques for quality data collection to ensure adequacy, accuracy and legitimacy of data.
• Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance
• Participate in code reviews and champion the adoption of best practices
• Applies in-depth knowledge of the business to design a data model that is appropriate for the project and translates business requirements into design specification documents to model the flow and storage of data across multiple data pipelines.
• Data engineers perform other duties as required, to meet team sprint goals

REQUIRED SKILLS/Qualifications:

• Bachelor’s degree in computer science, data or social science, operations research, statistics, applied mathematics, econometrics, or a related quantitative field AND 4+ years of experience in business analytics, data science, software development, data modeling and/or data engineering work OR Master's Degree in Computer Science, Math, Software is acceptable
• 5+ years of programming experience with command in at least two languages: SQL, Python, Java, R or Spark
• Expert proficiency in SQL; experience with Oracle, PostgreSQL, MySQL, or Microsoft SQL Server
• 4+ years of experience in at least one of the BI/Analytics space such as Azure Data Factory, Synapse, Data Explorer, Cosmos, App Insights, Power BI, and Databricks (or similar) (Note: Azure Data Factory and Databricks preferred)
• Experience using Git, or a comparable code repository
• Must be motivated, self-driven, curious, and creative
• Must be skilled communicator, and demonstrate an ability to work with end users and business leaders
• Demonstrate the ability to support and complement the work of a diverse development and/or operations team
• Experience working in a collaborative, cross-functional team; Active participation in sprint reviews
• Expert Knowledge and a minimum of four years’ experience in the following domains: Data management, software engineering, I&O (infrastructure and operations)

PREFERRED QUALIFICATIONS:

• Knowledge of health care operations
• Exposure to agile/scrum
• Interest and desire to contribute to emerging practices around DataOps (CI/CD, IaC, configuration management, etc.)
• Collaborate effectively with product management, program management, engineers, and stakeholders.
• Excellent analytical and critical thinking skills
• Ability to influence without authority and thrive in an ambiguous environment.