Lead Data Engineer/Architect

Hybrid in Lansing, MI, US • Posted 4 hours ago • Updated 4 hours ago
Contract W2
Contract Independent
Contract Corp To Corp
1 Year
No Travel Required
Hybrid
Depends on Experience
Fitment

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Job Details

Skills

  • Data engineer
  • AWS
  • Azure
  • Google
  • Spark
  • Kafka
  • Kubernetes
  • SageMaker
  • DBT
  • Juniper
  • data lakes
  • cloud service

Summary

Our client is looking a Data Engineer to lead excels in data modeling, Lakehouse and Medallion Architecture concepts, and data/ML products delivery using an agile DevOps framework with a mastery of distributed data architectures essential for data, analytical and operational ML applications with demonstrated proficiency in frameworks including Spark, Kafka, Kubernetes, SageMaker, DBT, Juniper Notebooks, Docker, SQL, and visualization tools such as Power BI/Tableau with the following track record:

Tasks

·        Data Engineering Lead excels in data modeling, Lakehouse, and ML products delivery using an agile DevOps framework with a mastery of distributed data architectures essential for data, analytical and operational ML applications with demonstrated proficiency in frameworks including DataBricks, Sagemaker, Spark, Kafka, Kubernetes, SQL, NoSQL DBs, Graph DBs, and visualization tools such as Power BI/Tableau.

·        Serve as the primary State of Michigan technology lead engaging with the UoM proof of concept team to support best practice adoption within the state hosting environment and provides training to DAV data engineers.

·        Oversee the design, development, and maintenance of data pipelines that move, transform, and prepare data for analytics and operational systems.

·        Architect and optimize data infrastructure, including storage solutions, orchestration frameworks, and ETL/ELT processes.

·        Ensure data quality, reliability, and security by establishing standards, monitoring systems, and implementing validation and governance practices.

·        Lead and mentor data engineering staff, providing technical guidance, reviewing designs/code, and supporting professional growth.

·        Collaborate with cross functional partners, such as data scientists, analysts, product teams, and business stakeholders, to ensure data solutions meet organizational needs and strategic goals.

Knowledge, Skills and Abilities Required:

·        Clear and concise written and verbal communication is crucial to success and productivity in this role

 

NOTE: Candidates must be local to the Lansing Michigan area and those willing to relocate. Candidates that relocate must relocate before day one and be ready to be on-site from day one at their own expense (non-negotiable). Wednesday and Thursday are REQUIRED in-office days. This is NON-NEGOTIABLE and there is NO remote only option.

 

Location: Lansing, MI  

Contract: 1 year

 

Skills Required:

·        4+ years - Hand-on experience is required in hydrating the enterprise Data Lake on a Cloud Service Provider (AWS, Azure, or Google) from relational, semi-structured and unstructured data sources by building Extract and Load Data Pipelines.

·        4+ years - Hands-on experience is required in Transforming the datasets in a Data Lake on a Cloud Service Provider to deliver Data Products with traceability of their attributes / features to the Critical Data Elements in the systems of record.

·        2+ years - Experience is required in enforcing Data Sharing Policies to Data Products to ensure that User get to see only the version of the Data Product the User is entitled to get access to at the time of subscription.

·        Experience in frameworks such as Spark, Kafka, Kubernetes, SageMaker, DBT, Juniper Notebooks, Docker, SQL

·        Experience with visualization tools such as Power BI/Tableau with the following track record

·        BS in Computer Science / Data Science / Information Systems with an overall 4+ years of experience

Skills Desired – A plus to have:

·        Proficiency desirable in DevOps tools including Github/Jenkins/Terraform/YAML/DAGs/Docker/Databricks/SageMaker etc. for building Data/ML pipelines to extract/store data from multiple sources to parquet destinations.

·        Experience desirable in promoting Data Engineering Standards and Best Practices among the community of developers to influence the enterprise towards building scalable and supportable Data/ML Products delivery and their usage by the community of data, analytics, and ML product users.

·        Experience desirable in implementing Data Governance and Data Security tools available on a CSP to automate the enforcement of Data Sharing Policies at the point of subscription of a Data Product by a subscriber.

·        Experience of minimum 4 years in modeling and leveraging Relational data services with demonstrated proficiency in Python/Pysparks/SQL programming and tuning SQL queries to extract data from multiple sources ( relational DB, flat files, CSV, HTML, JSON, etc) sources into Lakehouse Medallion architecture in parquet formats

·        Demonstrated experience and expertise of minimum 4 years in programming/scripting languages including Python, R, Spark, etc.

·        Experience in designing and delivering Star-schema based operational data store is required to enable visualization of program activities and outcomes in a visualization tool such as Power BI.

 

*** Rate depends on experience

*** Candidates authorized to work in the US are encouraged to apply. We can accept H1b, , TN, and other valid work visas for IT. However, we cannot accept OPT or CPT visas at this time.

*** Companies submitting candidates should only submit direct W2 employees for this position.

 

Please submit your resume by using the "URL" below

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10193654
  • Position Id: 10625MI-D
  • Posted 4 hours ago
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