Junior Data Engineer

About Infinitive:
Infinitive is a data and AI consultancy that enables its clients to modernize, monetize and operationalize their data to create lasting and substantial value. We possess deep industry and technology expertise to drive and sustain adoption of new capabilities. We match our people and personalities to our clients' culture while bringing the right mix of talent and skills to enable high return on investment.
Infinitive has been named “Best Small Firms to Work For” by Consulting Magazine 7 times most recently in 2024. Infinitive has also been named a Washington Post “Top Workplace”, Washington Business Journal “Best Places to Work”, and Virginia Business “Best Places to Work.”

Job Summary:
We are seeking a motivated Junior Data Engineer to support our data engineering initiatives by building and maintaining scalable data pipelines on AWS. The ideal candidate has 1–2 years of hands-on experience with Python, PySpark, and cloud-based data platforms, and is eager to grow their technical skills in a fast-paced, collaborative environment.

Key Responsibilities:

• Develop, test, and maintain data pipelines using Python and PySpark
• Ingest, transform, and clean structured and semi-structured data from multiple sources
• Collaborate with senior data engineers and analysts to support data infrastructure needs
• Deploy and monitor data workflows on AWS using services like S3, Lambda, Glue, and EMR
• Document processes, data models, and pipeline logic clearly for stakeholders
• Troubleshoot data issues and assist in performance tuning of jobs and queries

Required Qualifications:

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field
• 1–2 years of hands-on experience with Python and PySpark
• Working knowledge of AWS cloud services (e.g., S3, Lambda, Glue, EMR)
• Proficiency with SQL for querying and data manipulation
• Basic understanding of data warehousing concepts and ETL processes
• Familiarity with version control systems like Git

Preferred Qualifications:

• Experience with workflow orchestration tools like Apache Airflow or AWS Step Functions
• Exposure to data cataloging and metadata management tools
• Understanding of data lake and data warehouse architectures (e.g., Redshift, Snowflake, BigQuery)
• Ability to work in Agile development environments
• Strong problem-solving and communication skills

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