Sr Data Engineer

VSG Business Solutions LLC; Glendale (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

VSG Business Solutions LLC in Glendale, CA is seeking a seasoned Data Engineer to design, develop, and operate large-scale data pipelines. You will work with PySpark, Scala, SQL, and Python to deliver scalable data platform solutions for stakeholders.

You will contribute to Databricks governance, orchestration with Airflow (MWAA), and cloud-native data services across AWS and Kubernetes. A collaborative, Agile environment offers strong growth opportunities.

Qualifications

• 5+ years of data engineering experience building and operating large-scale pipelines.
• Deep hands-on Databricks and Spark (batch and streaming) experience.
• Strong understanding of Spark architecture and performance tuning.
• Proficient with Databricks tooling (API/SDK/CLI) for automation and governance.
• Advanced SQL with performance tuning and optimization.
• Production experience with Airflow (MWAA) for orchestration.
• Experience governing Databricks: Unity Catalog, ACLs, lineage, data privacy.
• Proficiency in Python and at least one other language (Scala, Kotlin, or SQL).
• Experience designing scalable ETL/ELT pipelines across diverse data sources.
• AWS experience; cloud and containerized services (Docker/Kubernetes).
• CI/CD and DevOps practices; data quality, monitoring, and logging.
• Self-starter with strong communication and Scrum/Agile familiarity.
• Snowflake familiarity is a plus.

Responsibilities

• Design, write, test, and deploy data pipelines using PySpark, Scala, SQL, Python.
• Meet with stakeholders to translate requirements into scalable data platform solutions.
• Understand Databricks tooling to diagnose errors and automate updates across pipelines.
• Explain Spark architecture and pipeline behavior to stakeholders for root-cause analysis.
• Provide solution architecture across AWS, Databricks, Kubernetes, and Airflow (MWAA).
• Manage Databricks governance: Unity Catalog, ACLs, lineage, data privacy tooling.
• Build and maintain Kubernetes containers and containerized utilities for data services.
• Troubleshoot connectivity and integration issues across platform components.
• Provision/remove access, monitor resources, and assess stakeholder requests.
• Collaborate across engineers, architects, and product managers in agile ceremonies.
• Document platform changes, standards, and pipeline configurations for data quality.

Skills

Databricks experience

Apache Airflow

Advanced SQL

Python

Spark / PySpark

Scala

Experience building and maintaining d

Education

Bachelor's Degree in Computer Science, Information Systems, or a related field, or equivalent work experience

Tools

Databricks

Apache Airflow

Spark

PySpark

SQL

Kubernetes

Docker

Job description

Mandatory skills

• Databricks experience (primary requirement)
• Apache Airflow
• Advanced SQL skills
• Python
• Spark / PySpark
• Scala
• Experience building and maintaining data pipelines and workflows

Key Responsibilities

• Design, write, test, and deploy data pipelines using PySpark, Scala, SQL, Python
• Meet with stakeholders to gather requirements and translate them into scalable data platform solutions
• Understanding of Databricks platform and developer tooling to diagnose errors, audit platform activity, and automate updates across pipelines, objects, and integrations
• Ability to explain Spark architecture and pipeline behavior to stakeholders to diagnose root causes and recommend solutions
• Provide solution architecture across AWS, Databricks, Kubernetes, and Airflow (MWAA), including cross-platform integrations
• Manage Databricks platform governance, including Unity Catalog, ACLs, lineage, and data discovery and privacy tooling
• Build and maintain Kubernetes containers and containerized utilities supporting deployed data platform services
• Apply networking knowledge to troubleshoot connectivity and integration errors across platform components
• Perform platform administration: provision and remove access, assess resource utilization, monitor platform health and cost, and evaluate stakeholder requests
• Collaborate with engineers, architects, and product managers to drive Core Data platform success; participate in agile/scrum ceremonies
• Maintain documentation of platform changes, standards, and pipeline configurations to support data quality and governance

Qualifications

• 5+ years of data engineering experience developing and operating large-scale data pipelines
• Deep hands-on experience with Databricks and Apache Spark (batch and streaming), including pipeline development in PySpark and/or Scala
• Strong understanding of Spark architecture-executors, stages, partitioning, shuffle, and performance tuning-with ability to explain tradeoffs to technical and non-technical stakeholders
• Proficiency with Databricks platform tooling (API, SDK, CLI) for automation, auditing, governance, and operational troubleshooting
• Proficient in SQL with advanced performance tuning capabilities
• Hands-on production experience with Airflow (MWAA) for orchestrating data pipelines
• Experience managing Databricks platform governance: ACLs, Unity Catalog, lineage, and access provisioning
• Proficiency in Python and at least one additional language (Scala, Kotlin, or SQL-driven pipeline tooling)
• Experience designing and optimizing scalable ETL/ELT pipelines integrating diverse structured and unstructured data sources
• AWS-primary experience (compute, storage, networking, IAM); experience with other cloud providers is transferable
• Proficiency with Docker and Kubernetes for building and maintaining containerized data platform services
• Working knowledge of networking concepts to diagnose cross-platform integration and connectivity issues
• Familiarity with Snowflake and comparable tooling relative to the Databricks ecosystem
• Experience designing and implementing CI/CD and DevOps practices (Git-based workflows)
• Experience implementing data quality checks, monitoring, and logging for pipeline reliability
• Self-starting problem solver with strong analytical and communication skills; willingness to learn new tooling and trends
• Familiar with Scrum and Agile methodologies
• Experience with Snowflake is a plus
• Bachelor's Degree in Computer Science, Information Systems, or a related field, or equivalent work experience, Master's Degree is a plus.