Job description

To Apply for this Job Click Here Job Title: Data Engineer Location Requirements: Hybrid Job Type: Contract Role Overview: You will collaborate with cross-functional teams to build scalable, efficient, and secure data systems. You’ll work with data across two cloud platforms—Azure and GCP—using various technologies. A key focus is on your expertise in python, Vertex AI, and advanced feature engineering techniques. Responsibilities: • Build and maintain scalable, reliable data pipelines for ingestion, transformation, and integration using tools like Kafka and Databricks. • Leverage innovative technologies to modernize and extend core data assets, including SQL-based, NoSQL-based, cloud-based, and real-time streaming platforms. • Develop and manage feature engineering pipelines for machine learning workflows with tools like Vertex AI, BigQuery ML, and custom Python libraries. • Design and implement automated testing frameworks for data quality, reliability, and organizational standards. • Optimize data workflows for performance, cost efficiency, and scalability across large datasets and complex environments. • Draft and review architectural diagrams, interface specifications, and other design documents to ensure clear communication of data solutions and technical requirements. Required Qualifications: • 4+ years of professional Data Development experience. • 4+ years of experience with SQL and NoSQL technologies. • 3+ years of building and maintaining data pipelines and workflows. • 2+ years of developing with Python. • Experience in feature engineering for machine learning pipelines. • Experience with CI/CD pipelines and processes. • Experience with automated unit, integration, and performance testing. • Experience with version control software such as Git. • Full understanding of ETL and Data Warehousing concepts. • Strong understanding of Agile principles (Scrum). To Apply for this Job Click Here Equal Employment Opportunity Statement Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.

Requirements

Must-haves

To Apply for this Job Click Here
Job Title: Data Engineer
Location Requirements: Hybrid
Job Type: Contract
Build and maintain scalable, reliable data pipelines for ingestion, transformation, and integration using tools like Kafka and Databricks.
Leverage innovative technologies to modernize and extend core data assets, including SQL-based, NoSQL-based, cloud-based, and real-time streaming platforms.
Develop and manage feature engineering pipelines for machine learning workflows with tools like Vertex AI, BigQuery ML, and custom Python libraries.
Design and implement automated testing frameworks for data quality, reliability, and organizational standards.
Optimize data workflows for performance, cost efficiency, and scalability across large datasets and complex environments.
Draft and review architectural diagrams, interface specifications, and other design documents to ensure clear communication of data solutions and technical requirements.
4+ years of professional Data Development experience.
4+ years of experience with SQL and NoSQL technologies.
3+ years of building and maintaining data pipelines and workflows.
2+ years of developing with Python.
Experience in feature engineering for machine learning pipelines.
Experience with CI/CD pipelines and processes.
Experience with automated unit, integration, and performance testing.
Experience with version control software such as Git.
Full understanding of ETL and Data Warehousing concepts.
Strong understanding of Agile principles (Scrum).
To Apply for this Job Click Here

Nice-to-haves

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Keywords to mirror

azuregcppythonaisqlmachine learningmlci/cdagilescrum

Platform: careers-page
Effort: medium