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Databricks Engineer

  • Databricks Engineer job type Posted on: Oct 12, 2026
  • Databricks Engineer experience level Openkyber
  • Databricks Engineer employment type Atlanta, Georgia
  • Databricks Engineer employment type Onsite
  • Databricks Engineer salary Full-time

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Job Title :

Databricks Engineer

Job Type :

Full-Time

Job Location :

Atlanta Georgia United States

Remote :

No

Jobcon Logo Job Description :

Please do not send your resume if you are not physically local to NYC/NJ as in-person interview is required.

Job Title - Data Engineer

Location - New York, NY (Hybrid)

Duration - 12+ Months

About the Role:

We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that power our analytics and machine learning capabilities. You will work cross-functionally with data scientists, analysts, and product teams to ensure data is reliable, accessible, and performant across the organization.

Key Responsibilities:

  • Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources.
  • Develop and manage data warehouses and data lakes using cloud platforms such as AWS, Google Cloud Platform, or Azure.
  • Ensure data quality, integrity, and availability through monitoring, testing, and alerting frameworks.
  • Collaborate with data scientists and analysts to understand data needs and deliver optimized data models.
  • Optimize query performance and storage efficiency across large-scale distributed systems.
  • Define and enforce data governance best practices, including lineage, cataloging, and documentation.
  • Partner with engineering teams to integrate data infrastructure with production systems.
  • Continuously evaluate and adopt new tools and technologies to improve the data platform.

Required Qualifications

  • 5+ years of experience in data engineering, software engineering, or a related field.
  • Proficiency in Python for data processing and pipeline development.
  • Strong SQL skills and experience with databases (e.g., SQL Server, Oracle, Redshift).
  • Experience with big data technologies such as Apache Spark, Kafka, or Flink.
  • Hands-on experience with cloud platforms (AWS, Google Cloud Platform, or Azure) and their data services.
  • Familiarity with version control (Git) and CI/CD practices.
  • Solid understanding of data modeling concepts (star schema, data vault, etc.).
  • Strong analytical and problem-solving skills with a focus on data quality and reliability.

Nice to Have:

  • Experience with dbt (data build tool) for transformation and data modeling.
  • Knowledge of streaming data architectures and real-time processing.
  • Familiarity with data observability tools such as Monte Carlo or Great Expectations.
  • Exposure to machine learning workflows and feature engineering pipelines.
  • Experience working in a fast-paced startup or high-growth environment.

For applications and inquiries,

Jobcon Logo Position Details

Posted:

Oct 12, 2026

Reference Number:

106584-38381

Employment:

Full-time

City:

Atlanta

Job Origin:

CIEPAL_ORGANIC_FEED

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Please do not send your resume if you are not physically local to NYC/NJ as in-person interview is required.

Job Title - Data Engineer

Location - New York, NY (Hybrid)

Duration - 12+ Months

About the Role:

We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that power our analytics and machine learning capabilities. You will work cross-functionally with data scientists, analysts, and product teams to ensure data is reliable, accessible, and performant across the organization.

Key Responsibilities:

  • Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources.
  • Develop and manage data warehouses and data lakes using cloud platforms such as AWS, Google Cloud Platform, or Azure.
  • Ensure data quality, integrity, and availability through monitoring, testing, and alerting frameworks.
  • Collaborate with data scientists and analysts to understand data needs and deliver optimized data models.
  • Optimize query performance and storage efficiency across large-scale distributed systems.
  • Define and enforce data governance best practices, including lineage, cataloging, and documentation.
  • Partner with engineering teams to integrate data infrastructure with production systems.
  • Continuously evaluate and adopt new tools and technologies to improve the data platform.

Required Qualifications

  • 5+ years of experience in data engineering, software engineering, or a related field.
  • Proficiency in Python for data processing and pipeline development.
  • Strong SQL skills and experience with databases (e.g., SQL Server, Oracle, Redshift).
  • Experience with big data technologies such as Apache Spark, Kafka, or Flink.
  • Hands-on experience with cloud platforms (AWS, Google Cloud Platform, or Azure) and their data services.
  • Familiarity with version control (Git) and CI/CD practices.
  • Solid understanding of data modeling concepts (star schema, data vault, etc.).
  • Strong analytical and problem-solving skills with a focus on data quality and reliability.

Nice to Have:

  • Experience with dbt (data build tool) for transformation and data modeling.
  • Knowledge of streaming data architectures and real-time processing.
  • Familiarity with data observability tools such as Monte Carlo or Great Expectations.
  • Exposure to machine learning workflows and feature engineering pipelines.
  • Experience working in a fast-paced startup or high-growth environment.

For applications and inquiries,

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