Junior-Mid Level Databricks Data Engineer- In MN, IA, WI, SD or ND!

Insight Global
Bloomington, MN, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Starter
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Third Normal Form Application Programming Interfaces (APIs) Data Analysis Automation of Tests Microsoft Azure Batch Processing Configuration Management Code Review Continuous Integration Information Engineering Data Governance Data Profiling
+41 more
Data Security Data Stores Relational Databases Revision Control Systems JSON Python (Programming Language) Machine Learning Microsoft SQL Server MongoDB NoSQL NumPy Oracle (Applications) Scrum Methodology Reliability Engineering Power BI DataOps SAP Sales and Distribution SQL Databases Software Technical Review Jupyter Notebook Parquet Data Processing Real Time Systems Data Ingestion Azure Data Factory Fast Healthcare Interoperability Resources Snowflake Apache Spark HybridCloud Git Powerquery Pandas Matplotlib Data Lakes Core Data Avro Real Time Data Data Delivery Data Pipelines Powerapps Databricks

Job description

Insight Global is seeking a Data Engineer to join a team of three data engineers and one business analyst working on interoperability projects, including a patient portal. This role will move data from the data lake into a FHIR server and expose it via APIs, contribute to building and exposing APIs for a patient portal, and design scalable data pipelines / work with real-time data.

Responsibilities: * 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. * Collaborate 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. * Help design and develop scalable, efficient data pipeline processes to manage data ingestion, cleansing, transformation, integration, and validation required to provide access to prepared data sets for analysts and data scientists. * Utilize development best practices including technical design reviews, implementing test plans, monitoring/alerting, peer code reviews, and documentation. * Collaborate with cross functional team to resolve data quality and operational issues and ensure timely delivery of products. * Incorporate core data management competencies including data governance, data security and data quality. * Participate in requirements gathering sessions with business and technical staff to distill technical requirements from business requests. * Assist Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.

Requirements

  • 2+ years’ experience in a hands-on data engineering role working with Python, SQL & Databricks * Experience with CI/CD and version control tools (Git preferred). * Demonstrate understanding of: * Data modeling techniques such as Star-/Snowflake-Schema, denormalized data modeling, 3NF etc. * Data formats such as Parquet, Avro, Delta, CSV, JSON, etc. * Data processing techniques like full-batch processing, time-based partitioning, distributed- and real-time processing etc. * Strong data profiling and analytic skills; ability to discover and highlight unique patterns/trends within data to identify and solve complex problems. Must be motivated, self-driven, curious, and creative. A skilled communicator to work with end users and partners, and to support and complement the work of a diverse development and/or operations team. * Knowledge of health care operations, specifically FHIR (Fast Healthcare Interoperability Resources) due to evolving regulations, highly preferred! * Exposure to Agile/Scrum * Experience with a hybrid cloud environment consisting of an on-premises and public cloud infrastructure. An ideal candidate will have experience with one or more of the following skill sets. * Experience with Relational databases like Oracle, SQL Server * Experience with Python (numpy, pandas, matplotlib etc.) and Jupyter notebooks for exploratory data analysis, machine learning, and process automation * Experience in areas of CI/CD, continuous testing, and site reliability engineering. * Familiarity in Microsoft Azure applications such as Azure Data Factory, Synapse, Purview, Databricks /Spark, Power BI, PowerApps. * Familiarity working with Document or NoSQL datastores, particularly MongoDB. * Familiarity in Power BI data models using advanced Power Query and DAX Interest and desire to contribute to emerging practices around DataOps (CI/CD, IaC, configuration management, etc.)

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