Junior Software/Data Engineer

Casual Precision; Shelton (CT); Hybrid; USD 65,000 - 100,000; Full time

Job summary

Casual Precision in Shelton, CT, is hiring a Junior Software/Data Engineer to help build and operate the CPDP. You will work across ingestion and transformation, turning raw data into trusted datasets used for attribution, analytics, and client delivery.

This engineering growth role emphasizes production Python, SQL, cloud data engineering, orchestration, and software practices, with mentorship from senior engineers and increasing ownership of the platform.

Qualifications

• 1–3 years experience in software or data engineering or related internship/project.
• Strong SQL including joins, CTEs, aggregations, and window functions.
• Working knowledge of Python and basic testing.
• Exposure to Spark/PySpark and orchestration tools like Airflow or Prefect.

Responsibilities

• Build and maintain AWS Glue PySpark ingestion jobs and Airflow DAGs for Bronze data loads.
• Develop dbt models to transform Bronze into Silver/Gold datasets with tests and docs.
• Migrate legacy SQL workflows to dbt and support AI-driven ingestion enhancements.
• Monitor data pipelines and platform health using CloudWatch and runbooks; assist in issue resolution.
• Support event ingestion components by investigating logs and applying fixes under review.
• Adhere to CI/CD processes and participate in code reviews and platform improvements.

Skills

SQL proficiency

Python programming

Airflow

Git & code reviews

Documentation

Curiosity & collaboration

Education

1–3 years experience in software/data roles

Tools

AWS Glue

dbt

Redshift

S3/Parquet

Airflow

Job description

Work Arrangement: Full-time, hybrid. You'll work from our Connecticut office several days each week, collaborating closely with senior engineers while maintaining flexibility to work remotely on other days.

About the Role

Casual Precision is hiring a Junior Software/Data Engineer to help build and operate the Casual Precision Data Platform (CPDP). You'll work across both sides of the data platform: ingestion (bringing operational and partner data into Bronze) and transformation (building dbt models that turn Bronze into trusted Silver and Gold datasets used for attribution, analytics, and client delivery).

This is an engineering growth role focused on production Python, SQL, cloud data engineering, orchestration, and software engineering practices—not dashboard development, BI, or analyst work. You'll work under the mentorship of senior engineers, delivering production code while steadily taking on greater ownership of the platform.

What You'll Do

• Build and maintain AWS Glue (PySpark) ingestion jobs and Airflow DAGs that load data into Bronze (S3/Parquet → Redshift) following established engineering patterns.
• Build and maintain dbt models that transform Bronze into trusted Silver and Gold datasets, including tests, documentation, and reusable Jinja components.
• Help migrate well-scoped legacy SQL workflows into dbt and support AI-assisted document ingestion enhancements when assigned.
• Monitor and troubleshoot data pipelines, dbt runs, and platform health using CloudWatch, Slack, and automated testing; resolve issues using runbooks and elevate when appropriate.
• Support our event ingestion platform (pixels and identity) by investigating logs, reproducing issues, and implementing small production fixes under review.
• Validate curated datasets with Analytics and BI teams while following platform standards, CI/CD practices, and Dev → Stage → Production deployment processes.
• Participate in code reviews, technical discussions, and continuous improvement of the CPDP platform.

Required Skills & Experience

• 1–3 years of experience in software engineering, data engineering, analytics engineering, or equivalent internship or academic project experience.
• Strong SQL including joins, CTEs, aggregations, and window functions.
• Working knowledge of Python, including scripting, packaging, and basic testing.
• Familiarity with Spark concepts through PySpark, AWS Glue, coursework, or personal projects.
• Exposure to workflow orchestration tools such as Airflow, Prefect, AWS Step Functions, or similar.
• Comfortable using Git, participating in code reviews, and delivering small, well-tested changes.
• Strong written communication for tickets, documentation, incident notes, and pull requests.
• Curious, collaborative, and comfortable learning across both ingestion and transformation engineering.

Nice to Have

• Hands-on AWS Glue or PySpark experience.
• Experience with dbt (projects, coursework, or internships).
• Experience with Redshift, Snowflake, BigQuery, or Databricks.
• Exposure to TypeScript, Node.js, or AWS Lambda.
• Familiarity with GitHub Actions or other CI/CD tooling.
• Tableau or BI experience as a consumer of curated datasets.
• Interest in advertising technology, attribution, identity, or media analytics.

What Success Looks Like

Within your first year, you'll be able to:

• Deliver production-ready ingestion jobs and dbt models independently.
• Diagnose and resolve common pipeline issues with minimal supervision.
• Write well-tested, documented Python and SQL that follows platform standards.
• Participate confidently in code reviews and technical discussions.
• Contribute ideas that improve the reliability, quality, and scalability of the platform.