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Principal Data Platform Engineer Jobs in Tennessee

Dollar General

Principal Data Engineer

Goodlettsville, TN · On-site

$107K - $129K/yr

Company Overview A Principal Data Engineer is responsible for expanding and optimizing data and ... cloud platform such as Snowflake / Azure or Databricks Qualifications: Work Experience &/or ...

Insight

Principal Data Scientist

Shelbyville, TN

Requisition Number: 105937 Principal Data Scientist Focus Clinical / HLS, Google Cloud Gen AI ... You will bridge the gap between clinical stakeholders, technical engineering teams, and executive ...

Oracle

Principal Data Engineer

Nashville, TN · On-site

$110K - $132K/yr

Data Pipeline and Solutions Engineering - Pipeline Design: * Leverages advanced knowledge of ETL processes to design, develop, and optimize automated, scalable, and efficient data pipeline ...

Oracle

Principal Data Engineer

Nashville, TN · On-site

Works independently and collaboratively in an agile development environment with other engineers to develop, maintain, and debug advanced data solutions that are scalable, efficient, cost effective ...

Oracle

Principal Platform Software Engineer

Nashville, TN · On-site

$130K - $174K/yr

We are seeking a Principal Platform Software Engineer (IC4) who enjoys building reliable software ... Strong fundamentals in data structures, algorithms, operating systems, networking, and distributed ...

Oracle

Principal Data Engineer

Nashville, TN · On-site

Works independently and collaboratively in an agile development environment with other engineers to develop, maintain, and debug advanced data solutions that are scalable, efficient, cost effective ...

Cadre5

Kubernetes Platform Engineer

Knoxville, TN

Kubernetes Platform Engineer Founded in 1999 in the beautiful Smoky Mountains of East Tennessee ... data sharing, and large-scale computational science across the U.S. Department of Energy (DOE)

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All JobsPrincipal Data Platform Engineer JobsPrincipal Data Platform Engineer Jobs in Tennessee

Principal Data Platform Engineer information

What is the difference between Principal Data Platform Engineer vs Data Engineer?

AspectPrincipal Data Platform EngineerData Engineer
CredentialsBachelor's/Master's in CS, Data Science, or related; often with certifications in cloud platformsBachelor's in CS, Data Science, or related; certifications are common but not mandatory
Work EnvironmentDesigns and oversees data platform architecture, leads technical strategyBuilds, maintains, and optimizes data pipelines and databases
Employer & Industry UsageUsed in large tech, finance, and enterprise companies focusing on scalable data solutionsCommon across industries for data processing and analytics tasks

The Principal Data Platform Engineer focuses on designing and leading the development of data platforms, ensuring scalability and performance. In contrast, Data Engineers primarily build and maintain data pipelines and infrastructure. Both roles require strong technical skills, but the Principal role involves strategic oversight and architecture leadership.

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Principal Data Platform Engineer jobs near you

Principal Data Engineer

∙ Elijah House Foundation

Goodlettsville, TN • On-site

$110 - $170/hr

Other

Posted 6 days ago

Job description

Company Overview

A Principal Data Engineer is responsible for expanding and optimizing data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. This role involves building and optimizing data systems from the ground up, ensuring that data delivery architecture is consistent throughout ongoing projects.

The Principal Data Engineer supports software developers, database architects, data analysts, and data scientists on data initiatives, ensuring optimal data delivery and architecture. This position requires expertise in data pipeline building and data wrangling, with a focus on enhancing data systems for improved efficiency and performance.

Job DetailsDuties & Responsibilities: What major responsibilities does this position have and what percentage of time is spent on completing them? (Typically 5-7)
  • Develop, construct, test, and maintain data architectures: responsible for creating and maintaining optimal data pipeline architectures necessary for the organization's operational efficiency. 65%
  • Collaborate with data scientists and other stakeholders: expected to collaborate with data scientists, business analysts, IT professionals, and management to assist with data-related technical issues and support their data infrastructure needs. 10%
  • Assemble and prepare large, complex data sets to meet functional business requirements: required to work with different teams to understand their data needs and ensure those needs are met. 10%
  • Build analytics tools: This will involve developing tools that utilize the data pipeline to provide actionable insights into key business performance metrics. 5%
  • Maintain data security and compliance: ensure systems meet industry practices and business requirements for data privacy and protection. 5%
  • Identify, design, and implement internal process improvements: This includes optimizing data delivery, automating manual processes, and re-designing infrastructure for greater scalability. 3%
  • Keep up-to-date with the latest technology trends: Continually learn and adapt to new technologies that could improve existing systems 2%
Knowledge, Skills and Abilities (KSAs): What KSAs are required to perform this job?
  • Hands on experience with programming languages (e.g. Python, SQL, GoLang)
  • Knowledge with SQL database design concepts and Data Models
  • Great numerical and analytical skills
  • Degree in Computer Science, IT, or similar field; a Master’s is a plus
  • Data engineering certification (e.g., Cloud Engineer, Data Engineer) is a plus
  • Experience with big data tools: Hadoop, Spark, Kafka, etc.
  • Experience with relational SQL and NoSQL databases, including MongoDG, Postgres and/or Cassandra.
  • Experience with data pipeline and workflow management tools: Airflow, Dataflow, Composer, etc.
  • Experience with GCP, Snowflake, Azure cloud services: BQ, Dataflow, Redshift
  • Experience with stream-processing systems: Kafka, Spark-Streaming, etc.
  • Good Knowledge of software engineering principles, methodologies and current best practices.
  • Able to multitask and shift priorities as needed.
  • Able to use BI Tools for data analysis and data QA.
Qualifications

Work Experience &/or Education: What are the minimum education and/or experience requirements necessary to perform this job?

  • 9+ years experience and a degree in information technology or computer science with additional vendor-specific certification.
  • BS or MS degree in Computer Science or a related technical field
  • 4+ years of Python or Java development experience
  • 4+ years of SQL experience (No-SQL experience is a plus)
  • 4+ years of experience with schema design and dimensional data modeling
  • Ability in managing and communicating data warehouse plans to internal clients
  • Experience designing, building, and maintaining data processing systems
  • Experience working with a cloud platform such as Snowflake / Azure or Databricks
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