Personify Health · 3 hours ago

Data Engineer II

United States

Full-time

Remote

Entry, Mid Level

$92K/yr - $95K/yr

2+ years exp

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ConsultingElectronic Health Record (EHR)

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Responsibilities

Perform development activities within a data engineering team and help guide, onboard, and train Data Engineer I.

Develop data pipelines and enhancements and investigate and troubleshoot issues, working closely with account management, ETL, data warehouse, business intelligence, and reporting teams.

Work with multiple data structures, including relational and non-relational models.

Do documentation, tech ops, sprints, implementation, monitor, QA, and related tasks.

Extracting, cleansing, and loading data.

Building data pipelines using SQL, Kafka, and other technologies.

Investigation and documentation of new data sets.

Triage incoming bugs and incidents.

Perform technical operation tasks.

Investigate and troubleshoot issues with data and data pipelines.

Participation in sprint refinement, planning, and kick-off to help estimate stories, raise awareness and additional implementation details.

Help monitor areas of the data pipeline and raise awareness to team when issues arise.

Performing and implementing new quality assurance rules to maintain consistent and accurate data.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data EngineeringSQLPythonExcelTableauMicroStrategyPowerBIREST APIJSONRelational ModelsNon-relational ModelsData QualityData CleansingData Pipelines

Required

Bachelor’s degree in Comp Sci, Comp Engr, Electronics Engr, IT, or related field, or foreign equivalent.

Requires 2 years of relevant experience in data engineering.

Must have skills via 2 years of experience in all of the following: examining data and code for quality and accuracy; modern relational and non-relational models; writing complex SQL, including pivots, window functions, and date calculations; Excel, Tableau, MicroStrategy, and PowerBI; REST API and JSON, and ability to parse that data and convert into relational models; and Python.