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Company

Original Job Post

RVO Health · 2 days ago

Staff Data Engineer

Minneapolis, MN

Full-time

Hybrid

Senior Level

$130K/yr - $180K/yr

7+ years exp

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Responsibilities

Provide technological ownership for data solutions on projects the team has been tasked with.

Formulate business and technical requirements with a cross-functional team of business analysts, architects, engineers, data analysts, and data scientists.

Architect and optimize data pipelines for performance and cost-efficiency within the Databricks environment.

Design and implement ETL processes using Databricks jobs to process and transform raw data into a usable format for analysis.

Design and build data pipelines from various data sources to a target data warehouse using batch data load strategies utilizing cutting-edge cloud technologies.

Document database designs that include data models, metadata, ETL specifications, and process flows for business data project integrations.

Perform periodic code reviews and test plans to ensure data quality and integrity.

Provide input into strategies as they drive the team forward with delivering business value and technical acumen.

Execute proof of concepts, where appropriate, to help improve our technical processes.

Conducted technical assessments and mentored junior team members.

Troubleshoot and support existing pipelines where required.

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 EngineeringSparkScalaPythonETL PipelinesApache SparkDelta LakeBig Data TechnologiesAWSAzureData ModelingTroubleshootingCloud Compute TechnologiesGitHubCI/CD ProcessesJob Orchestration TechnologiesTechnical LeadershipProblem-SolvingAnalyticalInterpersonalAdaptabilityTime Management

Required

7-10+ years of Data Engineering experience

4+ years of experience working on Spark (RDDs / Data Frames / Dataset API) using Scala/Python to build and maintain complex ETL pipelines

Deep understanding of Apache Spark, Delta Lake, and related big data technologies, and proficiency in modern programming languages such as Python and Scala

4+ years of experience in the big data space

3+ years of experience working on AWS (Kinesis / Kafka / S3 / RedShift) or Azure

Experience in translating business requirements into technical data solutions on a large scale

Experience creating data models within a data warehouse environment

Able to research and troubleshoot potential issues stakeholders present within the data ecosystem

Experience with cloud compute technologies like EMR and Databricks

Experience with GitHub and CI/CD processes

Experience working with job orchestration technologies (eg., Airflow / AWS Step Function)

Experience moving teams forward through technical implementations and thought leadership

Strong analytical and interpersonal skills

Able to work through ambiguity in a fast-paced, dynamically changing business environment

Ability to manage multiple tasks at the same time with minimal supervision