Junior Data Engineer

Artefact
United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Starter
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Airflow Amazon Web Services Microsoft Azure Big Data Continuous Integration Information Engineering Data Governance Data Retrieval Data Systems Python (Programming Language) Cloud Services SQL Databases
+8 more
Data Processing Azure Data Factory Snowflake Pyspark Information Technology AWS Glue Data Pipelines Databricks

Job description

We are looking for a Jr. Data Engineer to join our dynamic team. This role is ideal for someone with understanding of data engineering and a proven track record of working on data projects in a fast-paced environment., * Design, build, and maintain scalable and robust data pipelines using SQL, Python, Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and Pyspark.

  • Lead the integration of complex data systems and ensure consistency and accuracy of data across multiple platforms.
  • Implement continuous integration and continuous deployment (CI/CD) practices for data pipelines to improve efficiency and quality of data processing.
  • Work closely with data architects, analysts, and other stakeholders to understand business requirements and translate them into technical implementations.
  • Oversee and manage a team of data engineers, providing guidance and mentorship to ensure high-quality project deliverables.
  • Develop and enforce best practices in data governance, security, and compliance within the organization.
  • Optimize data retrieval and develop dashboards and reports for business teams.
  • Continuously evaluate new technologies and tools to enhance the capabilities of the data engineering function.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • 2+ years of industry experience in data engineering with a strong technical proficiency in SQL, Python, and big data technologies.
  • Experience with cloud services such as Azure Data Factory and AWS Glue.
  • Excellent problem-solving skills and the ability to work under tight deadlines.
  • Strong communication and interpersonal skills.

Preferred Qualifications: *

  • Certifications in Azure, AWS, or similar technologies.
  • Certifications in Databricks, Snowflake or similar technologies
  • Experience in the leading large scale data engineering projects

About the company

Artefact is a new generation of a data service provider, specializing in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organizations. We are proud to say that we’re enjoying skyrocketing growth.

Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet our clients’ specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we’ve acquired with our 300+ client base around the globe.

We have over 2000 employees across 16 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets: state of the art data technologies, lean AI agile methodologies for fast delivery, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts, all dedicated to bringing extra value to every client.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on dice.com

Good distractions

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

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · WWC Europe 2026

55 sec

Validating data processing architectures via containerized events

Modood Alvi · WWC 2025

4:32 min

Harnessing Spark with Python using PySpark and Py4J

Ayon Roy · LIVE

2:57 min

Core technical practices for robust data engineering

Sandhya Menon Sandhya Menon · WWC Europe 2026

3:37 min

Scaling machine learning pipelines from prototypes to petabytes

Julian Joseph · LIVE

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

Videos

See all

Related articles

See all