Data Engineer: ETL/PySpark & Cloud Data Pipelines

Novacruitix

Alabama

Hybrid

USD 90,000 - 120,000

Full time

6 days ago
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Job summary

Novacruitix is seeking a Data Engineer to design, develop, and maintain scalable ETL/ELT pipelines and cloud-based data solutions. You will work with large datasets from diverse sources and collaborate with analysts and data scientists to drive analytics and insights.

The role emphasizes building robust data workflows, data quality checks, and performance tuning, with onsite/hybrid/remote options based on client needs.

Qualifications

  • Strong experience with Python and SQL.
  • ETL / ELT development.
  • Apache Spark / PySpark.
  • Data Warehousing.
  • Cloud platforms: AWS, Azure, or GCP.
  • Databases such as SQL Server, PostgreSQL, Snowflake, or similar.
  • Experience with tools such as Databricks, Airflow, or Kafka is preferred.
  • Git and basic CI/CD knowledge.
  • Good communication and problem-solving skills.

Responsibilities

  • Design, develop, and maintain ETL/ELT data pipelines.
  • Work with large datasets from multiple sources.
  • Build and optimize data workflows for analytics and reporting.
  • Perform data transformation, validation, and quality checks.
  • Work closely with Data Analysts, Data Scientists, and application teams.
  • Troubleshoot and improve data pipeline performance.
  • Maintain technical documentation and follow data engineering best practices.

Skills

Python
SQL
ETL/ELT
Spark/PySpark
Data Warehousing
Cloud platforms
Databases (SQL Server, PostgreSQL,Snow
Databricks/Airflow/Kafka
Git/CI-CD
Communication/Problem-solving

Education

Bachelor's degree in CS/IT/Engineering

Tools

Databricks
Airflow
Kafka

Job description

Novacruitix is seeking a Data Engineer to design, develop, and maintain scalable ETL/ELT pipelines and cloud-based data solutions. You will work with large datasets from diverse sources and collaborate with analysts and data scientists to drive analytics and insights.

The role emphasizes building robust data workflows, data quality checks, and performance tuning, with onsite/hybrid/remote options based on client needs.

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