Infinitive Inc
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 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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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 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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