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Data & Analytics Engineer with Python

Ohm Systems
Woonsocket, RI, United States
6 days ago
Apply on www.careerjet.com
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source
www.careerjet.com

Tech stack

Data Analysis Microsoft Azure BigQuery Information Engineering Extract Transform Load (ETL) Data Transformation Data Migration Python (Programming Language) Cloudera SQL Databases Cloud Platform System Flask (Web Framework)
+3 more
Fastapi Data Analytics Microservices

Job description

  • Develop and optimize complex SQL, ETL/ELT, and data transformation processes.
  • Design data models, lineage, harmonization, and governance frameworks.
  • Lead data migration, mapping, reconciliation, and validation activities.
  • Build automated data quality and validation solutions.
  • Collaborate with business and engineering teams to deliver reliable data products.
  • Manage delivery, risks, dependencies, and issue resolution.

Requirements

  • 7+ years in Data Engineering, Analytics Engineering, or related fields.
  • Expert SQL and strong Python programming skills.
  • Hands-on experience with data modeling, data quality, lineage, and governance.
  • Experience building microservices using FastAPI or Flask.
  • Strong GCP experience (BigQuery, GKE, Dataproc, Composer).
  • Experience with Azure and cloud-based data platforms.
  • Proven expertise in ETL/ELT, data migration, reconciliation, and validation frameworks.
  • Strong analytical, communication, stakeholder management, and delivery leadership skills.

Apply for this position

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Apply on www.careerjet.com
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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

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3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

3:33 min

Connecting frontends via a FastAPI proxy backend layer

Saoussen Chaabnia Saoussen Chaabnia · Europe 2026 Virtual

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Leveraging BigQuery ML for scalable SQL-based segmentation experiments

Julian Joseph · LIVE

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Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

1:42 min

Introduction to the fast API web framework

Sebastián Ramírez · World Congress 2022

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Explaining query execution overhead and caching limitations in BigQuery

Adnan Rahic · JS Congress

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LIVE • over 3 years ago

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World Congress 2026 Europe • about 2 months ago

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World Congress 2022 • about 4 years ago

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World Congress 2024 • about 2 years ago

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