Job description
Data Engineer I
Who we are
Jellyvision ALEX®, is on a mission to improve lives by helping people choose and use their benefits. We are raising the bar—for benefits and the employee experience (for our employees and those of the customers we serve) – by scaling personalization, compassion and an earnest intent to be helpful in all that we do.
Jellyvision people are a group of creative problem solvers who use good judgment, give each other honest feedback, engage in real debate, and snack frequently. We are curious, hungry, and humble—because we know this is how we’ll continue to make an impact. We’re kind, biased towards action, and sweat the details to create great experiences for those we serve.
We are an inclusive, human-first workplace. Respect and trust for each other are foundational, and our equitable total rewards offerings support the lives and holistic well-being of our unique people. At Jellyvision, expect career experiences that challenge you, empower you to have a direct impact on our mission, and enable you to learn, try, and do while having fun along the way.
What’s the role?
As a Data Engineer I, you’ll help build and maintain the data infrastructure that enables our teams to personalize benefits for millions of users. This is an early-career role focused on developing strong data engineering fundamentals - building pipelines, designing storage structures, and modeling data that power products, client analytics, and strategic decisions. You’ll work closely with the rest of our data team to deliver reliable, well-structured data across the organization.
What you’ll do to be successful
1.) Build and maintain data pipelines and storage
- Build, test, and deploy Airflow DAGs in MWAA following team standards
- Write clean, production-ready Parquet files using PyArrow or Spark with proper compression and partitioning
- Implement ETL/ELT pipelines from source → landing → transformed layers
- Help maintain S3 storage structures following existing partitioning, lifecycle, and access policies
- Assist with dimensional modeling—turn normalized data into star-schema facts and dimensions under senior guidance
- Implement basic data quality checks using Python
- Troubleshoot failing DAGs, rerun backfills, and respond to alerts
- Participate in on-call support rotation
- Update and maintain pipeline documentation
KPIs: pipeline reliability, on-time deliver, code quality
2.) Learn, collaborate, and help grow our data platform
- Participate in code reviews to learn best practices and improve code quality
- Partner with Senior Data Engineers and Analytics Engineers on architecture alignment
- Work with analytics and product teams to understand and deliver data requirements
- Document troubleshooting procedures and platform patterns
- Contribute to sprint planning and technical discussions
KPIs: documentation quality, responsiveness to feedback, stakeholder satisfaction
Experience & skills you’ll need
Required:
- 2+ years of practical experience (professional, internship, and bootcamps count)
- Solid Python and working SQL proficiency
- Familiarity with cloud platforms (AWS/GCP/Azure) and modern data tooling (e.g Airflow, dbt, Spark, Snowflake, Databricks, Redshift)
- Understanding of data modeling concepts (e.g., star schema, normalization) and ETL/ELTdesign practices
- Experience reading/writing Parquet
- Ability to write and run basic Airflow DAGs
- Docker fundamentals
- Git fundamentals, agile development and CI/CD practices
- Demonstrated curiosity
- Genuine tinkerer energy: you’ve built personal data projects for fun, tried random tools (Polars, DuckDB, Ollama, local LLMs, MotherDuck, etc.), and probably have a messy but awesome docker-compose.yml on your machine
Nice to Have:
- Experience with AI coding assistants
- Exposure to AI tools (MCP servers, Ollama, local LLMs)
- Knowledge of Delta Lake or Snowflake clustering
- Basic Terraform experience
- Simple data-quality tooling
The Details
- Location: Remote, Chicago-based preferred for occasional in-office days.
- Starting Salary: $95,000 - $110,000
What Jellyvision will give you
Check out our benefits here!
Jellyvision is committed to continuous evolution and fostering a more diverse and inclusive workplace where everyone is welcomed, valued, and respected. It doesn’t matter your race, ethnicity, religion, age, disability, sexual orientation, gender, gender identity/expression, country of origin, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), criminal histories consistent with legal requirements or any other basis protected by law…we just want amazing people who are willing to grow along with us.
Although we have a Chicago-based HQ that employees are welcome to work out of whether they’re local or just visiting, this position is also eligible for work by a remote employee out of CA, CO, FL, GA, IL, IN, KY, MI, MN, NC, NY, OH, OR, PA, SC, TN, TX, UT, VA, WA or WI.
