Full Stack Software Engineer

VDart Inc; United States; Hybrid; USD 140,000 - 180,000; Full time

Job summary

VDart Inc. is seeking a Full Stack Data Engineer to design and operate end-to-end data pipelines in a hybrid model ( Bloomington, IL, 90% remote, 10% in-office). The role emphasizes strong AWS data services, PySpark, Spark, Airflow, and data lakehouse patterns.

Duration is 6 months with collaboration across analysts and engineers. The ideal candidate will mentor peers, optimize pipelines, and contribute to production reliability while leveraging dbt for transformations and IaC with Terraform or

Qualifications

• Experience with AWS data services (S3, Redshift, Glue, EMR, Kinesis, Athena, Lake Formation, Step Functions, Lambda).
• Advanced Python (PySpark, boto3) and SQL skills including window functions and query optimization.
• Proficient with Spark for batch/streaming and performance tuning.
• Experience with Airflow or equivalents (Prefect, Dagster) for pipeline orchestration.
• Data modeling using star/snowflake schemas; data lakehouse design (Iceberg/Delta Lake/Hudi).
• Infrastructure as code with Terraform or AWS CDK.
• CI/CD with GitHub Actions or AWS CodePipeline; automated testing for pipelines.
• Data transformation tooling with dbt (preferred).

Responsibilities

• Independently design and deliver end-to-end data pipelines from ingestion to analytics.
• Collaborate with analysts, scientists, and business stakeholders to shape data products.
• Mentor junior engineers and perform code reviews; drive production issue resolution.

Skills

AWS Data Services

Python (PySpark, boto3)

SQL (window functions, query tuning)

Apache Spark

Airflow MWAA / Dagster / Prefect

Dimensional modeling

Data pipelines design

dbt

End-to-end data pipelines

Kinesis / Lambda / Glue

Tools

Terraform

AWS CDK

GitHub Actions

AWS CodePipeline

MWAA

Job description

Job Title: Full Stack Software Engineer

Location: Bloomington, IL (90% remote and 10% in-office)

Duration: 6 Months

Must-Have Technical Skills:

• AWS Data Services: S3, Redshift, Glue, EMR, Kinesis, Athena, Lake Formation, Step Functions, Lambda
• Programming: Python (PySpark, boto3) advanced proficiency; SQL (window functions, query optimization)
• Big Data / Spark: Apache Spark - batch and streaming; performance tuning
• Pipeline Orchestration: Apache Airflow (MWAA) or equivalent (Prefect / Dagster)
• Data Modeling: Dimensional modeling (star/snowflake schema); data lakehouse design (Iceberg / Delta Lake / Hudi)
• Infrastructure as Code: Terraform or AWS CDK - mandatory
• CI/CD: GitHub Actions, AWS CodePipeline, or equivalent; automated testing for pipelines
• Data Transformation: dbt (preferred)

Good to Have:

• Snowflake or Databricks experience alongside AWS
• Apache Kafka / Amazon MSK for streaming pipelines
• AWS SageMaker or ML pipeline support experience
• Multi-cloud or on-prem to AWS migration experience

Soft Skills & Expectations:

• Ability to independently design and deliver end-to-end data pipelines
• Strong communication skills to engage with analysts, scientists, and business stakeholders
• Experience mentoring junior engineers and conducting code reviews
• Proven track record of debugging and resolving production pipeline issues

Key Skills: Data Engineer, AWS SageMaker, Apache Kafka, Databricks