Senior Data Engineer III: Scalable Pipelines & Cloud

HTC Global Services

Dearborn (MI)

On-site

USD 110,000 - 150,000

Full time

5 days ago
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Benefits offered by this job

Health benefits
401(k) matching
Paid time off

Job summary

HTC Global Services is seeking a Data Engineer III in Dearborn, MI to design, build, and maintain scalable data infrastructure and pipelines. You will work with cloud platforms (GCP, BigQuery) and modern data tooling to collect, store, and analyze large data volumes, collaborating with stakeholders to ensure data quality and governance.

The role emphasizes ingestion pipelines, data models, and automated processes, with opportunities to drive efficiency and innovative data solutions across the

Qualifications

  • 7+ years of data engineering experience.
  • Bachelor's degree required.
  • Experience with Google Cloud Platform (GCP) and BigQuery.
  • Experience with Kafka and cloud-based data platforms.
  • Strong SQL, Python, Java, and APIs experience.
  • Familiarity with Agile development and data governance.

Responsibilities

  • Design, build, and maintain scalable data infrastructure and pipelines.
  • Develop and manage cloud-based data platforms for ingestion and curation.
  • Collaborate with stakeholders to define data requirements and solutions.
  • Implement data governance, security, and IaC practices.
  • Optimize data quality, performance, and cost-efficiency.

Skills

Data engineering
Big data
Python
Java
SQL
APIs
Agile
Cloud architecture
AI / Expert systems

Education

Bachelor's degree

Tools

GCP
BigQuery
Cloud Run
Kafka
Dataflow
Pub/Sub
Cloud Functions
DBT/Dataform
IaC

Job description

HTC Global Services is seeking a Data Engineer III in Dearborn, MI to design, build, and maintain scalable data infrastructure and pipelines. You will work with cloud platforms (GCP, BigQuery) and modern data tooling to collect, store, and analyze large data volumes, collaborating with stakeholders to ensure data quality and governance.

The role emphasizes ingestion pipelines, data models, and automated processes, with opportunities to drive efficiency and innovative data solutions across the

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